Search results for: optimization planning

Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

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Authors: Maziar Yazdani, Ahmad Khodaee, Fatemeh Hajizadeh

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The purpose of this research was analysis of the reliability of the signaling system in the railway and planning repair and maintenance of its subsystems. For this purpose, it will be endeavored to introduce practical strategies for activities control and appropriate planning for repair and preventive maintenance by statistical modeling of reliability. Therefore, modeling, evaluation, and promotion of reliability of the signaling system appear very critical. Among the key goals of the railway is provision of quality service for passengers and this purpose is gained by increasing reliability, availability, maintainability and safety of (RAMS). In this research, data were analyzed, and the reliability of the subsystems and entire system was calculated and with emphasis on preservation of performance of each of the subsystems with a reliability of 80%, a plan for repair and preventive maintenance of the subsystems of the signaling system was introduced.

Keywords: reliability, modeling reliability, plan for repair and preventive maintenance, signaling system

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Authors: A. Cerrato Casado, C. Guigou, P. Jean

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In this investigation, the particle swarm optimization (PSO) algorithm is used to perform the inversion of the dispersion curves in the spectral analysis of surface waves (SASW) method. This inverse problem usually presents complicated solution spaces with many local minima that make difficult the convergence to the correct solution. PSO is a metaheuristic method that was originally designed to simulate social behavior but has demonstrated powerful capabilities to solve inverse problems with complex space solution and a high number of variables. The dispersion curve of the synthetic soils is constructed by the vertical flexibility coefficient method, which is especially convenient for soils where the stiffness does not increase gradually with depth. The reason is that these types of soil profiles are not normally dispersive since the dominant mode of Rayleigh waves is usually not coincident with the fundamental mode. Multiple synthetic soil profiles have been tested to show the characteristics of the convergence process and assess the accuracy of the final soil profile. In addition, the inversion procedure is applied to multiple real soils and the final profile compared with the available information. The combination of the vertical flexibility coefficient method to obtain the dispersion curve and the PSO algorithm to carry out the inversion process proves to be a robust procedure that is able to provide good solutions for complex soil profiles even with scarce prior information.

Keywords: dispersion, inverse problem, particle swarm optimization, SASW, soil profile

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Authors: Taye O. Famuditi, Jonathan Potts, Malcolm Bray

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This paper examines the shoreline management planning policy in England and its suitability for ameliorating the diverse environmental problems associated with Nigeria’s coastal zones. It examines the success of SMPs in England since the mid-1990s and progress achieved, with the aim of understudying the current management approach that can be transferred to Nigeria to strengthen its adoption, and as a necessary corollary, implementation of the SMPs. This paper also examines key elements of the shoreline management frameworks in England and provides answers to the question: Would shoreline management planning approach in England be appropriate and feasible in Nigeria? It further concludes that many of the action plans and principles of participation should be adoptable provided that a participatory approach that involves all stakeholders including community members and relevant sectorial ministries as well as appropriate legal framework is encouraged.

Keywords: shoreline management plans, coastal zone management, stakeholder engagement, participatory approach, Nigeria

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Authors: Jie-Ying Wu, Kuo-Hao Weng, Jin-Cheng Fu

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This study proposes changes to land use for the purposes of water retention and runoff reduction, with the aim of reducing the frequency of flooding. This study uses the Zhuoshui River in Taiwan as a case study, designing different land use planning strategies, and setting up various detention spaces. The HEC-HMS model developed by the Hydrology Research Center of the U.S. Army Corps of Engineers is used to calculate the decrease in runoff using various planning strategies, during five precipitation events of increasing return periods. This study finds that a maximum decrease in runoff of 14 million square meters can result by changing the form of land cover and storm detention in non-urban agricultural and river zones. This is due to the fact that non-urban land accounts for 96% of the area under study. Greatest efficacy was demonstrated in a two-year return period, with results ranging from 16% to 52%. The efficacy of a 100-year return period rated from 3% to 8%. Urban area detentions consist of agricultural paddy fields, storm water ponds and rainwater retention systems in building basements. Although urban areas can provide one million cubic meters of runoff storage, this result is insignificant due to the fact that urban area constitutes only 4% of the study area. By changing land cover, a 2-year return period has a 9% efficacy, and a 100-year return period has a 2% efficacy.

Keywords: flood detention space, land-use, spatial planning, Zhuoshuei River, Taiwan

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Norhayati Mohd Rasip, Abd. Samad Hasan Basari , Nuzulha Khilwani Ibrahim, Burairah Hussin

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The allocation of working schedule especially for shift environment is hard to fulfill its fairness among them. In the case of nurse scheduling, to set up the working time table for them is time consuming and complicated, which consider many factors including rules, regulation and human factor. The scenario is more complicated since most nurses are women which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect patient's life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to solve nurse scheduling problem. The result shows that the generated multiple initial schedule is fulfilled the requirements and produces the lowest cost of constraint violation.

Keywords: nurse scheduling, particle swarm optimisation, nurse rostering, hard and soft constraint

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Authors: Nadhir Al-Ansari, Ammar A. Ali, Sven Knutsson

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Iraq is located in the Middle East. It covers an area of 433,970 square kilometres populated by about 32 million inhabitants. Iraq greatly relies in its water resources on the Tigris and Euphrates Rivers. Recently, Iraq is suffering from water shortage problems. This is due to external and internal factors. The former includes global warming and water resources policies of neighbouring countries while the latter includes mismanagement of its water resources. The supply and demand are predicted to be 43 and 66.8 Billion Cubic Meters (BCM) respectively in 2015, while in 2025 it will be 17.61 and 77 BCM respectively. In addition, future prediction suggests that Tigris and Euphrates Rivers will be completely dry in 2040. To overcome this problem, prudent water management policies are to be adopted. This includes Strategic Water Management Vision, development of irrigation techniques, reduction of water losses, use of non-conventional water resources and research and development planning.

Keywords: Iraq, Tigris River, Euphrates River, water scarcity, water resources management

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal

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The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP

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Authors: Samain Sabrin, Joshua Pratt, Joshua Bryk, Maryam Karimi

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Globally, extreme heat events have led to a surge in the number of heat-related moralities. These incidents are further exacerbated in high-density population centers due to the Urban Heat Island (UHI) effect. Varieties of anthropogenic activities such as unsupervised land surface modifications, expansion of impervious areas, and lack of use of vegetation are all contributors to an increase in the amount of heat flux trapped by an urban canopy which intensifies the UHI effect. This project aims to propose a systematic approach to measure the impact of air quality and increased temperature based on urban morphology in the selected metropolitan cities. This project will measure the impact of build environment for urban and regional planning using human biometeorological evaluations (mean radiant temperature, Tmrt). We utilized the Rayman model (capable of calculating short and long wave radiation fluxes affecting the human body) to estimate the Tmrt in an urban environment incorporating location and height of buildings and trees as a supplemental tool in urban planning, and street design. Our current results suggest a strong correlation between building height and increased surface temperature in megacities. This model will help with; 1. Quantify the impacts of the built environment and surface properties on surrounding temperature, 2. Identify priority urban neighborhoods by analyzing Tmrt and air quality data at pedestrian level, 3. Characterizing the need for urban green infrastructure or better urban planning- maximizing the cooling benefit from existing Urban Green Infrastructure (UGI), and 4. Developing a hierarchy of streets for new UGI integration and propose new UGI based on site characteristics and cooling potential.

Keywords: air quality, heat mitigation, human-biometeorological indices, increased temperature, mean radiant temperature, radiation flux, sustainable development, thermal comfort, urban canopy, urban planning

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Authors: Dong Yue, Hua Chen

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The study region Xihu Harbor in Xiangshan County, Ningbo City is located in the central coast of Zhejiang Province. Concerning the wave dispating issue, Ningbo government firstly introduced Spartina alterniflora in 1980s. In the 1990s, S. alterniflora spread so rapidly thus a ‘grassland’ in the sea has been created nowadays. It has become the most important invasive plant of China’s coastal tidal flats. Although S. alterniflora had some ecological and economic functions, it has also brought series of hazards. It has ecological hazards on many aspects, including biomass and biodiversity, hydrodynamic force and sedimentation process, nutrient cycling of tidal flat, succession sequence of soil and plants and so on. On engineering, it courses problems of poor drainage and channel blocking. On economy, the hazard mainly reflected in the threat on aquaculture industry. The purpose of this study is to explore an ecological, feasible and economical way to manage Spartina alterniflora and use the land formed by it, taking Xihu Harbor in Xiangshan County as a case. Comparison method, mathematical modeling, qualitative and quantitative analysis are utilized to proceed the study. Main outcomes are as follows. By comparing a series of S. alterniflora managing methods which include the combination of mechanical cutting and hydraulic reclamation, waterlogging, herbicide and biological substitution from three standpoints – ecology, engineering and economy. It is inferred that the combination of mechanical cutting and hydraulic reclamation is among the top rank of S. alternifora managing methods. The combination of mechanical cutting and hydraulic reclamation means using large-scale mechanical equipment like large screw seagoing dredger to excavate the S. alterniflora with root and mud together. Then the mix of mud and grass was blown off nearby coastal tidal zone transported by pipelines, which can cushion the silt of tidal zone to form a land. However, as man-made land by coast, the reclamation area’s ecological sensitivity is quite high and will face high possibility of flood threat. Therefore, the reclamation area has many reasonability requirements, including ones on location, specific scope, water surface rate, direction of main watercourse, site of water-gate, the ratio of ecological land to urban construction land. These requirements all became important basis when the planning was being made. The water system planning, green space system planning, road structure and land use all need to accommodate the ecological requests. Besides, the profits from the formed land is the managing project’s source of funding, so how to utilize land efficiently is another considered point in the planning. It is concluded that by aiming at managing a large area of S. alterniflora, the combination of mechanical cutting and hydraulic reclamation is an ecological, feasible and economical method. The planning of reclamation area should fully respect the natural environment and possible disasters. Then the planning which makes land use efficient, reasonable, ecological will promote the development of the area’s city construction.

Keywords: ecological management, ecological planning method, reclamation area, Spartina alternifora, Xihu harbor

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Authors: Yanqun Li, Hong Geng

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The rapid urbanization process taking big cities as the main body leads to the unequal configuration of urban and rural areas in the aspects of land supply, industrial division of labor, service supply and space allocation, and induces the shrinking characterization of service energy, industrial system and population vitality in small towns. As an important spatial unit in the spectrum of urbanization that serves, connects and couples urban and rural areas, the shrinking phenomenon faced by small towns has an important influence on the healthy development of urbanization. Based on the census of small towns in Wuhan metropolitan area, we have found that the shrinking of small towns is a passive contraction of elastic tension under the squeeze in cities. Once affected by the external forces such as policy regulation, planning guidance, and population return, small towns will achieve expansion and growth. Based on the theory of complex adaptive systems, this paper comprehensively constructs the development index evaluation system of small towns from five aspects of population, economy, space, society and ecology, measures the shrinking level of small towns, further analyzes the shrinking characteristics of small towns, and identifies whether the shrinking is elastic or not. And then this paper measures the resilience ability index of small town contract from the above-mentioned five aspects. Finally, this paper proposes an adaptive mechanism of urban-rural interaction evolution under fine division of labor to response the passive shrinking in small towns of Wuhan. Based on the above, the paper creatively puts forward the planning response measures of the small towns on the aspects of spatial layout, function orientation and service support, which can provide reference for other regions.

Keywords: complex adaptive systems, resiliency shrinking, adaptation mechanism, planning response

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Authors: Hoang Vo Thi Minh, Duyen Nguyen Thi Phuong, Gerardo Van Halsema

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As one of the deltas which is extremely vulnerable to climate change, the Mekong Delta, Vietnam is facing many challenges that need to be addressed in strategic and holistic ways. In this study scope, a strategic delta planning is recently considered as a new vision of Adaptive Delta Management for the Mekong Delta. In Adaptive Delta Management, Room for the Rivers (RftR) has been formulated as a typical innovation, which is currently in need of careful consideration for implementing in the Mekong Delta’s planning process. This study then attempts to investigate the roles and analyze sociological aspects of the RftR as potential strategic 'soft' measure, in upstream of Hau River in An Phu district, An Giang province, especially in terms of its so-called multifunctions. The study applied social science approach embedded with a few qualitative methods including in-depth interviews and questionnaire distribution and conjoint analysis as a quantitative approach. The former mainly aims at gaining the local community’s perceptions about the RftR solution. The latter tries to gain farmers’ willingness to accept (WTA) with regard to their level of preference towards the three selected solutions which are considered as strategic plans for sustainably developing the MD. Qualitative data analysis shows that, farmers perceive RftR as very useful for their livelihoods due to its multifunctions as well as in terms of water management. The quantitative results illustrated that respondents expressed their WTAs on RftR as 84. 240 thousand VND / year. Amongst the three solutions that are analysed within this study (Floating rice for upper delta, Room for the Rivers for the Middle, and Shrimp-Mangrove integration for the coastal delta), RfrR was ranked as second preference from respondents. This result is not exactly reflecting the real values of these three mentioned solutions but showing a tendency that can be seen as a reference for the decision-makers in delta planning processes.

Keywords: strategic delta planning, room for the River, farmers’ perception, willingness-to-accept, local livelihoods

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Authors: H. Nikzad, S. Yoshitomi

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This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.

Keywords: design constraints, ETABS, linear static analysis, MATLAB, RC shear wall-frame structures, structural optimization

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Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

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Authors: Saqib Ali

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Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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Authors: F. Gökgöz, M. E. Atmaca

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Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: electricity market, portfolio optimization, risk management, value at risk

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Authors: Florian Gschösser, Walter Purrer

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The paper shows examples for the (environmental) optimization of production processes for asphalt mixtures applied for typical road pavements in Austria and Switzerland. The conducted “from-cradle-to-gate” LCA firstly analyzes the production one cubic meter of asphalt and secondly all material production processes for exemplary highway pavements applied in Austria and Switzerland. It is shown that environmental impacts can be reduced by the application of reclaimed asphalt pavement (RAP) and by the optimization of specific production characteristics, e.g. the reduction of the initial moisture of the mineral aggregate and the reduction of the mixing temperature by the application of low-viscosity and foam bitumen. The results of the LCA study demonstrate reduction potentials per cubic meter asphalt of up to 57 % (Global Warming Potential–GWP) and 77 % (Ozone depletion–ODP). The analysis per square meter of asphalt pavement determined environmental potentials of up to 40 % (GWP) and 56 % (ODP).

Keywords: asphalt mixtures, environmental potentials, life cycle assessment, material production

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: J. Van Engeland, C. Lavigne, S. De Jaeger

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In the light of the transition towards a more circular economy, recovery of products, parts or materials will gain in importance. Additionally, the EU proximity principle related to waste management and emissions generated by transporting large amounts of end-of-life products, shift attention to local recovery networks. The Flemish inter-communal cooperation for municipal solid waste management Meetjesland (IVM) is currently investigating the set-up of such a network. More specifically, the network encompasses the recycling of polyvinyl chloride (PVC), which is collected in separate containers. When these containers are full, a truck should transport them to the processor which can recycle the PVC into new products. This paper proposes a model to optimize the container collection. The containers are located at different Civic Amenity sites (CA sites) in a certain region. Since people can drop off their waste at these CA sites, the containers will gradually fill up during a planning horizon. If a certain container is full, it has to be collected and replaced by an empty container. The collected waste is then transported to a single processor. To perform this collection and transportation of containers, the responsible firm has a set of vehicles stationed at a single depot and different personnel crews. A vehicle can load exactly one container. If a trailer is attached to the vehicle, it can load an additional container. Each day of the planning horizon, the different crews and vehicles leave the depot to collect containers at the different sites. After loading one or two containers, the crew has to drive to the processor for unloading the waste and to pick up empty containers. Afterwards, the crew can again visit sites or it can return to the depot to end its collection work for that day. All along the collection process, the crew has to respect the opening hours of the sites. In order to allow for some flexibility, a crew is allowed to wait a certain amount of time at the gate of a site until it opens. The problem described can be modelled as a variant to the PVRP-TW (Periodic Vehicle Routing Problem with Time Windows). However, a vehicle can at maximum load two containers, hence only two subsequent site visits are possible. For that reason, we will refer to the model as a model for building tactical waste collection schemes. The goal is to a find a schedule describing which crew should visit which CA site on which day to minimize the number of trucks and the routing costs. The model was coded in IBM CPLEX Optimization studio and applied to a number of test instances. Good results were obtained, and specific suggestions concerning route and truck costs could be made. For a large range of input parameters, collection schemes using two trucks are obtained.

Keywords: container collection, crew scheduling, mixed integer linear programming, waste management

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Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

Abstract:

Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Herawanti Kumalasari, Raldi Hendro Koestoer, Hayati Sari Hasibuan

Abstract:

Geographically, Indonesia is located in the arc of volcanoes that cause disaster prone one of them is landslide disaster. One of the causes of the landslide is the conversion of land from forest to agricultural land in upland areas and river border that has a steep slope. The study area is located in the highlands with fertile soil conditions, so most of the land is used as agricultural land and plantations. Land use transfer also occurs around the geothermal field in Pangalengan District, West Java Province which will threaten the sustainability of geothermal energy utilization and the safety of the community. The purpose of this research is to arrange the concept of spatial pattern arrangement in the geothermal area based on disaster mitigation. This research method using superimpose analysis. Superimpose analysis to know the basic physical condition of the planned area through the overlay of disaster risk map with the map of the plan of spatial plan pattern of Bandung Regency Spatial Plan. The results of the analysis will then be analyzed spatially. The results have shown that most of the study areas were at moderate risk level. Planning of spatial pattern of existing study area has not fully considering the spread of disaster risk that there are settlement area and the agricultural area which is in high landslide risk area. The concept of the arrangement of the spatial pattern of the study area will use zoning system which is divided into three zones namely core zone, buffer zone and development zone.

Keywords: spatial planning, geothermal, disaster risk, zoning

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Authors: Kevin Worrall, Euan McGookin

Abstract:

The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

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Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

Abstract:

Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

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Authors: Giuseppe Timperio, Robert De Souza

Abstract:

The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Minakshi Goswami, M. V. Khire

Abstract:

The urban land use is an outcome of geographical and socio economic factors over the decades. Hence, spatial information on land use and possibilities of alternate use is essential for the selection, planning and implementation to meet the increasing demands of human needs and welfare of the urban area. This information assists in monitoring the land use resulting out of charging demands of increasing urban population over the decades. So in this paper, a detailed work on urban land use pattern, with a special reference to build up land in Bangalore city is analyzed in view of the various master plans from 1975to 2011. An attempt has been made to study the status of urban land use of Bangalore city during this period to detect the changes on land utilization rate that has taken place in each master plan period, particularly in the built-up land. The set of measures taken by the city corporation to contain the problems regarding the extremely bothering existing land use in Bangalore city is analyzed.

Keywords: built up land, land use changes, master plan, population

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Authors: Mehrzad Soltani, Pegah Rezaei

Abstract:

In the endeavor to construct cities that are not only thriving but also environmentally responsible, effective urban planning and architectural design assume paramount significance. The focal point of this pursuit is the harnessing of urban renewable energy. By embracing sustainable practices such as the integration of solar panels into the urban landscape and the establishment of smart grids, cities are poised to confront head-on the dual challenge of surging energy demands and pressing environmental concerns. Urban renewable energy solutions offer a multifaceted approach to these issues. Firstly, they usher in a clean and sustainable source of energy, reducing the cities' ecological footprint while ensuring a continuous power supply. This transition to eco-friendly energy is also intrinsically linked to enhanced spatial utilization, thereby streamlining the efficiency of urban areas. Moreover, it spurs the adoption of sustainable transportation alternatives, diminishing the reliance on fossil fuels and mitigating air pollution. However, the significance of integrating renewable energy solutions transcends the realm of urban sustainability. It embodies a holistic approach towards creating cities that harmoniously coexist with the natural environment while catering to the needs and aspirations of their inhabitants. In essence, prioritizing sustainability in urban planning and architectural design has evolved from a choice to a necessity, one that not only safeguards the cities' well-being but also fosters a better quality of life for their residents. Thus, it is imperative that we acknowledge the transformative potential of these innovations as we pave the way towards the cities of the future.

Keywords: sustainability, smart grids, solar panel, urban planning, environmental concerns

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Authors: Celine Delacroix

Abstract:

Analyses of global emission scenarios demonstrate that slowing population growth could lead to substantial emissions reductions and play an important role to avoid dangerous climate change. For this reason, the advancement of individual reproductive rights might represent a valid climate change mitigation and adaptation option. With this focus, we reflected on population ethics and the ethical dilemmas associated with environmental degradation and climate change. We conducted a mixed-methods qualitative data study consisting of an online survey followed by in-depth interviews with stakeholders of the reproductive health and rights and environmental sustainability movements to capture the ways in which the linkages between family planning, population growth, and environmental sustainability are perceived by these actors. We found that the multi-layered marginalization of this issue resulted in two processes, the polarization of opinions and its eschewal from the public fora through population reductionism. Our results indicate that stakeholders of the reproductive rights and environmental sustainability movements find that population size and family planning influence environmental sustainability and overwhelmingly find that the reproductive health and rights ideological framework should be integrated in a wider sustainability frame reflecting environmental considerations. This position, whilst majoritarily shared by all participants, was more likely to be adopted by stakeholders of the environmental sustainability sector than those from the reproductive health and rights sector. We conclude that these processes, taken in the context of a context of a climate emergency, threaten to weaken the reproductive health and rights movement.

Keywords: environmental sustainability, family planning, population growth, population ethics, reproductive rights

Procedia PDF Downloads 150