Search results for: revenue optimization

Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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Authors: Anupam Purwar

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In conventional consumer product industry, stockouts are taken care by carrying buffer stock to check underserving caused by changes in customer demand, incorrect forecast or variability in lead times. But, for food outlets, the alternate of carrying buffer stock is unviable because of indispensable need to serve freshly cooked meals. Besides, the food outlet being the sole provider has no incentives to reduce stockouts, as they have no fear of losing revenue, gross profit, customers and market share. Hence, innovative, easy to implement and practical ways of addressing the twin problem of long queues and poor customer experience needs to be investigated. Current work analyses the demand pattern of 11 different food items across a routine day. Based on this optimum resource allocation for all food items has been carried out by solving a linear programming problem with cost minimization as the objective. Concurrently, recommendations have been devised to address this demand and supply side problem keeping in mind their practicability. Currently, the recommendations are being discussed and implemented at ISB (Indian School of Business) Hyderabad campus.

Keywords: F&B industry, resource allocation, demand management, linear programming, LP, queuing analysis

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Authors: Michalis Michael, Mauro Overend

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Buildings, in which we spend 87-90% of our time, act as a shelter protecting us from environmental conditions and weather phenomena. The building's overall performance is significantly dependent on the envelope’s glazing part, which is particularly critical as it is the most vulnerable part to heat gain and heat loss. However, conventional glazing technologies have relatively low-performance thermo-optical characteristics. In this regard, during winter, the heat losses due to the glazing part of a building envelope are significantly increased as well as the heat gains during the summer period. In this study, the contribution of an innovative glazing technology, namely Closed Cavity Façade (CCF) in improving energy efficiency and IEQ in office buildings is examined, aiming to optimize various design configurations of CCF. Using Energy Plus and IDA ICE packages, the performance of several CCF configurations and geometries for various climate types were investigated, aiming to identify the optimum solution. The model used for the simulations and optimization process was MATELab, a recently constructed outdoor test facility at the University of Cambridge (UK). The model was previously experimentally calibrated. The study revealed that the use of CCF technology instead of conventional double or triple glazing leads to important benefits. Particularly, the replacement of the traditional glazing units, used as the baseline, with the optimal configuration of CCF led to a decrease in energy consumption in the range of 18-37% (depending on the location). This mainly occurs due to integrating shading devices in the cavity and applying proper glass coatings and control strategies, which lead to improvement of thermal transmittance and g-value of the glazing. Since the solar gain through the façade is the main contributor to energy consumption during cooling periods, it was observed that a higher energy improvement is achieved in cooling-dominated locations. Furthermore, it was shown that a suitable selection of the constituents of a closed cavity façade, such as the colour and type of shading devices and the type of coatings, leads to an additional improvement of its thermal performance, avoiding overheating phenomena and consequently ensuring temperatures in the glass cavity below the critical value, and reducing the radiant discomfort providing extra benefits in terms of Indoor Environmental Quality (IEQ).

Keywords: building energy efficiency, closed cavity façade, optimization, occupants comfort

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Authors: Nassali Celine Lindah

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The study sought to find out how public accountability is a challenge to sustainable development in Uganda. The study was guided by the following set of objectives included establishing the challenges of Public accountability, the importance of accountability in Uganda, and the possible solutions to the problems identified in the study. In order to ensure proper accountability there should be proper control of resources, specifically the control of both public revenue and expenditures. Stakeholders should also be involved in the accountability process. Accountability can reduce corruption and other abuses, assure compliance with standards and procedures, and improve performance and organizational learning. The study involved qualitative and quantitative data collection techniques. A sample of 20 respondents from various districts/towns was used using both technical staff and non-technical staff members. The study utilized secondary and primary data, which was obtained using interviews and observations. The study reached a conclusion that the major challenges of Public accountability in Uganda are poor leadership, poor resource management, unethical behavior by the government officials and political involvement, among others. The study also recommended that the policymakers should design relevant guidelines/policies to help promote the process of public accountability in Uganda like prosecution and convictions, strengthen public expenditure management benchmarking and performance measurements, among others.

Keywords: accountability, sustainability, government activities, government sector

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Authors: Aadiv Shah, Hari Nair, Vedant Mittal, Alice Cheeran

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Present-day agricultural practices such as blanket spraying not only lead to excessive usage of pesticides but also harm the overall crop yield. This paper introduces an algorithm to optimize the traversal of an unmanned aerial vehicle (UAV) in constrained environments. The proposed system focuses on the agricultural application of targeted spraying for locust elimination. Given a satellite image of a farm, target zones that are prone to locust swarm formation are detected through the calculation of the normalized difference vegetation index (NDVI). This is followed by determining the optimal path for traversal of a UAV through these target zones using the proposed algorithm in order to perform pesticide spraying in the most efficient manner possible. Unlike the classic travelling salesman problem involving point-to-point optimization, the proposed algorithm determines an optimal path for multiple regions, independent of its geometry. Finally, the paper explores the idea of implementing reinforcement learning to model complex environmental behaviour and make the path planning mechanism for UAVs agnostic to external environment changes. This system not only presents a solution to the enormous losses incurred due to locust attacks but also an efficient way to automate agricultural practices across the globe in order to improve farmer ergonomics.

Keywords: locust, NDVI, optimization, path planning, reinforcement learning, UAV

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Authors: Lei Xue, Liye Zhao, Jundong Wang, Yu Xue

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A hybrid energy conversion system composed of a floating offshore wind turbine (FOWT) and wave energy converters (WECs) may possibly reduce the levelized cost of energy, improving the platform dynamics and increasing the capacity to harvest energy. This paper investigates the aerodynamic performance and dynamic responses of the combined semi-submersible FOWT and point-absorber WECs in frequency and time domains using synthetic optimizing control under turbulent wind and irregular wave conditions. Individual pitch control is applied to the FOWT part, while spring–damping control is used on the WECs part, as well as the synergistic control effect of both are studied. The effect of the above control optimization is analyzed under several typical working conditions, such as below-rated wind speed, rated wind speed, and above-rated wind speed by OpenFAST and WEC-Sim software. Particularly, the wind-wave misalignment is also comparatively investigated, which has demonstrated the importance of applying proper integrated optimal control in this hybrid energy system. More specifically, the combination of individual pitch control and spring–damping control is able to mitigate the platform pitch motion and improve output power. However, the increase in blade root load needs to be considered which needs further investigations in the future.

Keywords: floating offshore wind turbine, wave energy converters, control optimization, individual pitch control, dynamic response

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Authors: Melody Mandevere, Roselyn Cheruiyot

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Through Corporate Social Responsibility (CSR), organizations contribute to a stable environment that leads to a predictable climate for investment and trade. Organizations are now deviating from traditional CSR, where it was believed that the only responsibility of an organization is to meet its shareholder's needs. Organizations and society now believe that an organization has many stakeholders that it must satisfy for it to be viable. The function of State-Owned Enterprises (SOEs) is not profit making but providing service and accomplishing public policy objectives. SOEs demand consideration in the current economic climate because they represent an important part of the economies of many countries. Given the importance and complex relationship of the stakeholders in SOE, the paper seeks to examine how full name first Zimra is implementing its CSR activities. SOE managers are responsible for CSR implementation and stakeholder engagement. ZIMRA is one of the parastatals that plays a crucial role in the Zimbabwean economy. It is, therefore, important to understand how Zimra is implementing CSR. Qualitative research was used for the research. Interviews were contacted with Zimra managers to understand how they are implementing CSR. Although Zimra managers understand the CSR concept, the organization does not have a CSR strategy that includes their stakeholders, which may have a negative impact on stakeholder perception and the organization's reputation. The funding of the CSR strategy is also not sustainable.

Keywords: corporate social responsibility, managers, stakeholders, state-owned enterprises

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Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

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A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

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Authors: Mark E. Lokanan, Liz Lee

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This paper aims to examine the role of accountants as gatekeepers in anti-money laundering compliance in real estate transactions. The paper seeks to answer questions on ways in which accountants are involved in real estate transactions and mandatory compliance with regulatory authorities in Canada. The data for the study came from semi-structured interviews with accountants, lawyers, and government officials. Preliminary results reveal that there is a conflict between accountants’ obligation to disclose and loyalty to their clients. Accountants often do not see why they are obligated to disclose their clients' information to government agencies. The importance of the client in terms of the amount of revenue contributed to the accounting firm also plays a significant role in accountants' reporting decision-making process. Although the involvement of accountants in real estate purchase and sale transactions is limited to lawyers or notaries, they are often involved in designing financing schemes, which may involve money laundering activities. The paper is of wider public policy interests to both accountants and regulators. It is hard not to see Chartered Professional Accountant (CPA) Canada and government regulators using the findings to better understand the decision-making processes of accountants in their reporting practices to regulatory authorities.

Keywords: money laundering, real estate, disclosure, legislation, compliance

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: Nermin A. Morsy, Amany N. Beshay

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The tourism industry has seen considerable transformations due to the emergency of e-commerce. For instance, airlines are increasingly dependent on achieving online sales instead of their traditional platform. Online travel agencies’ (OTAs) websites have been able to reach a broader range of customers and generate more revenue. Therefore, website quality plays an important role in attaining website effectiveness. It is now considered as a critical factor in attracting customers' attention and build loyalty. Customers are more likely to visit and purchase at websites that exhibit highly desirable qualities. A user-friendly website can help tourists find their target information easily and make decisions quickly. This research focuses on analyzing the impact of airline and OTAs’ websites quality on the actual customer usage and purchase intentions. An online survey was distributed among internet users to assess the various dimensions of website quality in the context of online booking and their effect on customer’s usage and purchase intentions. The data from the survey was analyzed statistically using correlation, t-tests and other statistical tests. Results revealed the direct impact of website quality on customer usage and purchase intentions.

Keywords: airlines, OTAs, purchasing intention, website quality

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Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

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This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Ilhan Keskin, Hasan Bulent Kantarci

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In this study, one of the tools of Islamic financing known as “Sukuk” a non-interest bearing investment which has started to be implemented in Turkey and the world as a whole is discussed. In order to increase the vitality and efficiency of the economy, by taking lessons from the recent economic crisis new developments in the banking and investment sector are being expanded. The purpose of all investors is to obtain more revenue through the use of capital. The inability of traditional investment tools to meet the expectations of investors and the interest based financial system where one investor benefits at the expense of another there has been the need for a different, reliable and non-interest bearing financial market that is consistent with the Islamic rule. As a result an alternative and more reliable interest free financing tool “Sukuk” rental certificates covering people who are sensitive to Islamic rules, appeal to all segments, hidden remaining capital that contributes to the economy, reduce disparities in income distribution, common risk sharing system of profit and loss sharing has emerged. Today, for the structural countries by examining the state of the world market economy the applicability, enactment and future issues associated with this attractive kind of Islamic finance namely the “Sukuk” market has been explained.

Keywords: Islamic finance, islamic markets, non-interest bearing, rental certificates

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Siamak Eskandari, Neda Ebadi

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Among common electronic parts which have been invented and have made a great revolution in the lighting system through the world, certainly LEDs have no rival. These small parts with their very low power consumption, very dazzling and powerful light and small size and with their extremely high lifetime- compared to incandescent bulbs and compact fluorescent lamp (CFLs) have undoubtedly revolutionized the lighting industry of the world. Based on conducted studies and experiments, in addition to their acceptable light and low power consumption -compared to incandescent bulbs and CFLs-, they have very low and in some cases zero environmental pollution and negative effects on human beings. Because of their longevity, in the case of using high-quality circuits and proper and consistent use of LEDs in conventional and intelligent buildings, there will be no need to replace the burnout lamps, for a long time (10 years). In this study which was conducted on 10-watt power LEDs with suitable heatsink/cooling, considerable amount of heat was generated during lighting after 5 minutes and 45 seconds. The temperature rose to above 99 degrees Celsius and this amount of heat can raise the water temperature to 60 degrees Celsius and more. Based on conducted experiments, this can provide the heat required for bathing, washing, radiators (in cold seasons) easily and only by imposing very low cost and it will be a big step in the optimization of energy consumption in the future.

Keywords: energy, light, water, optimization of power LED

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Authors: Feijoo E. Colomine Duran, Carlos E. Peñaloza Corredor

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There modeling component selection financial investment (Portfolio) a variety of problems that can be addressed with optimization techniques under evolutionary schemes. For his feature, the problem of selection of investment components of a dichotomous relationship between two elements that are opposed: The Portfolio Performance and Risk presented by choosing it. This relationship was modeled by Markowitz through a media problem (Performance) - variance (risk), ie must Maximize Performance and Minimize Risk. This research included the study and implementation of multi-objective evolutionary techniques to solve these problems, taking as experimental framework financial market equities Colombia Stock Exchange between 2009-2015. Comparisons three multiobjective evolutionary algorithms, namely the Nondominated Sorting Genetic Algorithm II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Indicator-Based Selection in Multiobjective Search (IBEA) were performed using two measures well known performance: The Hypervolume indicator and R_2 indicator, also it became a nonparametric statistical analysis and the Wilcoxon rank-sum test. The comparative analysis also includes an evaluation of the financial efficiency of the investment portfolio chosen by the implementation of various algorithms through the Sharpe ratio. It is shown that the portfolio provided by the implementation of the algorithms mentioned above is very well located between the different stock indices provided by the Colombia Stock Exchange.

Keywords: finance, optimization, portfolio, Markowitz, evolutionary algorithms

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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The use of Micro Gas Turbine (MGT) as the engine in Unmanned Aerobic Vehicles (UAVs) and power source in Robotics is widespread these days. Research has been conducted in the past decade or so to improve the performance of different components of MGT. This type of engine has interrelated components which have non-linear characteristics. Therefore, the overall engine performance depends on the individual engine element’s performance. Computational Fluid Dynamics (CFD) is one of the simulation method tools used to analyze or even optimize MGT system performance. In this study, the compressor of the MGT is designed, and performance optimization is being done using CFD. Performance of the micro compressor is improved in order to increase the overall performance of MGT. A high value of pressure ratio is to be achieved by studying the effect of change of different operating parameters like mass flow rate and revolutions per minute (RPM) and aerodynamical and geometrical parameters on the pressure ratio of the compressor. Two types of compressor designs are considered in this study; 3D centrifugal and ‘planar’ designs. For a 10 mm impeller, the planar model is the simplest compressor model with the ease in manufacturability. On the other hand, 3D centrifugal model, although more efficient, is very difficult to manufacture using current microfabrication resources. Therefore, the planar model is the best-suited model for a micro compressor. So. a planar micro compressor has been designed that has a good pressure ratio, and it is easy to manufacture using current microfabrication technologies. Future work is to fabricate the compressor to get experimental results and validate the theoretical model.

Keywords: computational fluid dynamics, microfabrication, MEMS, unmanned aerobic vehicles

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Authors: Gupta Amit, Kumar Ramesh, P. C. Tewari

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model-based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies Economic Order Quantity (EOQ), Just in Time (JIT), Vendor Managed Inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: inventory policy, ranking, DBA, selection criteria

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Younis Elhaddad, Alfonso Ortega

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Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.

Keywords: evolutionary automatic programming, gas lift, genetic algorithms, oil production

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

Abstract:

The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Maciej Dudek, Robert Kruszewski, Janusz Kudla, Konrad Walczyk

Abstract:

In this paper, we study how taxation of bequests affects human capital formation in the long term and short term horizon. Our underlying model is an overlapping generation model (OLG) with some degree of altruism on the part of the ancestors' generation towards their descendants. We ask the question in three separate frameworks. First, we study a simple one-sector model where a proxy of human capital is wage income. It the steady-state -for CRRA utility function and human capital produced with non-decreasing returns -the taxation of bequests is neutral to the accumulation of human capital. In the second framework, neutrality applies to the growth rates of human capital, physical capital, and consumption. In this case, taxation increases the level of bequests, leading to a lower value of current consumption. Finally in we consider two periods model instead of infinite horizon model as long as the tax revenue is at least partially rebated back to the public, the fraction of human capital engaged in the process of formation of human capital increases with the tax rate on bequests. In other words, taxation of bequests is partially offset by an increase in human capital formation. Higher human capital allows the future generation to earn higher wages, and today's generation can find it optimal to endow the future generation with more human capital when taxation is imposed on physical capital transferred to the next generation.

Keywords: taxation, bequests, policy, human capital

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Authors: Sina Keyhanian, Abbas Ahmadi, Behrooz Karimi

Abstract:

We present a multi-objective binary programming model which considers surgical cases are scheduling among operating rooms and the configuration of surgical instruments in limited capacity hospital trays, simultaneously. Many mathematical models have been developed previously in the literature addressing different challenges in health-care logistics such as assigning operating rooms, leveling beds, etc. But what happens inside the operating rooms along with the inventory management of required instruments for various operations, and also their integration with surgical scheduling have been poorly discussed. Our model considers the minimization of movements between trays during a surgery which recalls the famous cell formation problem in group technology. This assumption can also provide a major potential contribution to robotic surgeries. The tray configuration problem which consumes surgical instruments requirement plan (SIRP) and sequence of surgical procedures based on required instruments (SIRO) is nested inside the bin packing problem. This modeling approach helps us understand that most of the same-output solutions will not be necessarily identical when it comes to the rearrangement of surgeries among rooms. A numerical example has been dealt with via a proposed nested simulated annealing (SA) optimization approach which provides insights about how various configurations inside a solution can alter the optimal condition.

Keywords: health-care logistics, hospital tray configuration, off-line bin packing, simulated annealing optimization, surgical case scheduling

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Authors: Prabha Rohatgi

Abstract:

To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Ying-Pin Chang

Abstract:

This paper presents a method for combining a particle swarm optimization with nonlinear time-varying evolution and orthogonal arrays (PSO-NTVEOA) in the planning of harmonic filters for the high speed railway traction system with specially connected transformers in unbalanced three-phase power systems. The objective is to minimize the cost of the filter, the filters loss, the total harmonic distortion of currents and voltages at each bus simultaneously. An orthogonal array is first conducted to obtain the initial solution set. The set is then treated as the initial training sample. Next, the PSO-NTVEOA method parameters are determined by using matrix experiments with an orthogonal array, in which a minimal number of experiments would have an effect that approximates the full factorial experiments. This PSO-NTVEOA method is then applied to design optimal harmonic filters in Taiwan High Speed Rail (THSR) traction system, where both rectifiers and inverters with IGBT are used. From the results of the illustrative examples, the feasibility of the PSO-NTVEOA to design an optimal passive harmonic filter of THSR system is verified and the design approach can greatly reduce the harmonic distortion. Three design schemes are compared that V-V connection suppressing the 3rd order harmonic, and Scott and Le Blanc connection for the harmonic improvement is better than the V-V connection.

Keywords: harmonic filters, particle swarm optimization, nonlinear time-varying evolution, orthogonal arrays, specially connected transformers

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Authors: E Tolufase

Abstract:

The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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Authors: Ali Heidari

Abstract:

This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

Procedia PDF Downloads 225