Search results for: stakeholders problem solving

Authors: Sourabh Joshi, Geetinder Kaur, Sarabjit Kaur, Gulwatanpreet Singh, Geetika Mannan

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In this paper, we have use an algorithm that able to obtain an optimal solution to travelling salesman problem from a huge search space, quickly. This algorithm is based upon the ant colony optimization technique and employees roulette wheel selection mechanism. To illustrate it more clearly, a program has been implemented which is based upon this algorithm, that presents the changing process of route iteration in a more intuitive way. In the event, we had find the optimal path between hundred cities and also calculate the distance between two cities.

Keywords: ant colony, optimization, travelling salesman problem, roulette wheel selection

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Michael F. Mascolo

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Western democratic traditions are being strained. Western nations are losing the common agonistic ground needed to engage in traditional forms of democracy – adversarial debate, voting, and the peaceful transfer of power. Political polarization among party elites has become commonplace. Because it seeks to resolve conflict through the integration of opposites, a dialectical approach to resolving partisan conflict offers the promise of helping political partisans bridge ideological divides. This paper contains an analysis of dialectical engagement as a collaborative alternative to adversarial politics. Dialectical engagement involves two broad phases: collaborative political problem-solving and dialectical problem-solving. The paper contains a description of an 18-month longitudinal study assessing the effectiveness of dialectical engagement as a method for bridging divides on contentious socio-political issues. The study shows how dialectical engagement produced dramatic consensus among a small group of individuals from different political orientations as they worked together to resolve the issue of capital punishment.

Keywords: collaborative democracy, dialectical thinking, capital punishment, partisan conflict

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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This study explores the pseudo-geometric version of the extensively researched Traveling Salesman Problem (TSP), proposing a novel generalization of existing algorithms which are traditionally confined to the geometric version. By adapting the "onion husk" method and introducing auxiliary algorithms, this research fills a notable gap in the existing literature. Through computational experiments using randomly generated data, several metrics were analyzed to validate the proposed approach's efficacy. Preliminary results align with expected outcomes, indicating a promising advancement in TSP solutions.

Keywords: optimization problems, traveling salesman problem, heuristic algorithms, “onion husk” algorithm, pseudo-geometric version

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Authors: John McNamara

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Growing up creative is an important idea in today’s classrooms. As education seeks to prepare children for their futures, it is important that the system considers traditional as well as non-traditional pathways. This poster describes the findings of a research study investigating creative potential in children with learning disabilities. Children with learning disabilities were administered the Torrance Test of Creative Problem Solving along with subtests from the Comprehensive Test of Phonological Processing. A quantitative comparative analysis was computed using paired-sample t-tests. Results indicated statistically significant difference between children’s creative problem-solving skills and their reading-based skills. The results lend support to the idea that children with learning disabilities have inherent strengths in the area of creativity. It can be hypothesized that the success of these children may be associated with the notion that they are using a type of neurological processing that is not otherwise used in academic tasks. Children with learning disabilities, a presumed left-side neurological processing problem, process information with the right side of the brain – even with tasks that should be processed with the left side (i.e. language). In over-using their right hemisphere, it is hypothesized that children with learning disabilities have well-developed right hemispheres and, as such, have strengths associated with this type of processing, such as innovation and creativity. The current study lends support to the notion that children with learning disabilities may be particularly primed to succeed in areas that call on creativity and creative thinking.

Keywords: learning disabilities, educational psychology, education, creativity

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Zainab Olabisi Tairu

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Strategic partnerships are a core requirement in delivering sustainable tourism for development in developing nations like Papua New Guinea. This paper unveils the strategic partnerships for sustainable tourism development in Papua New Guinea. Much emphasis is made among tourism stakeholders, on the importance of strategic partnership and positioning in developing sustainable tourism development. This paper engages stakeholders’ ecotourism differentiation and power relations in the discussion of the paper through interviews and observations with tourism stakeholders in Papua New Guinea. Collaborative approaches in terms of sustaining the tourism industry, having a milestone of achieved plans, are needed for tourism growth and development. This paper adds a new insight to the body of knowledge on stakeholders’ identification, formation, power relations and an integrated approach to successful tourism development. In order to achieve responsible tourism planning and management outcomes, partnerships must be holistic in perspective and based on sustainable development principles.

Keywords: stakeholders, sustainable tourism, Papua New Guinea, partnerships

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Authors: Zhuoran Li, Guan Qin

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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.

Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method

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Authors: Lidimma Benjamin, Nimmyel Gwakzing, Wuyep Nanyi

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Technical and Vocational Education and Training (TVET) has many stakeholders, each with their own values and interests. This study will focus on the diversity of the values and interests within and across groups of stakeholders by quantifying the value that stakeholders attached to several quality attributes of TVET, and also find out to what extent TVET stakeholders differ in their values. The quality of TVET therefore, depends on how well it aligns with the values and interests of these stakeholders. The five stakeholders are parents, students, teachers, policy makers, and work place training supervisors. The 9 attributes are employer appreciation of students, graduation rate, obtained computer skills of students, mentoring hours in workplace learning/Students Industrial Work Experience Scheme (SIWES), challenge, structure, students’ appreciation of teachers, schooling hours, and attention to civic education. 346 respondents (comprising Parents, Students, Teachers, Policy Makers, and Workplace Training Supervisors) were repeatedly asked to rank a set of 4 programs, each with a specific value on the nine quality indicators. Conjoint analysis was used to obtain the values that the stakeholders assigned to the 9 attributes when evaluating the quality of TVET programs. Rank-ordered logistic regression was the statistical/tool used for ranking the respondents values assign to the attributes. The similarities and diversity in values and interests of the different stakeholders will be of use by both Nigerian government and TVET colleges, to improve the overall quality of education and the match between vocational programs and their stakeholders simultaneous evaluation and combination of information in product attributes. Such approach models the decision environment by confronting a respondent with choices that are close to real-life choices. Therefore, it is more realistically than traditional survey methods.

Keywords: TVET, vignette study, conjoint analysis, quality perception, educational stakeholders

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

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Authors: Ali Abbas

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Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. In out current environment, the path from a phenomenon to value involves numerous people with expertise in various areas including domain knowledge of a field and the ability to make decisions within an operating environment that lead to value creation. We propose some skills that industrial engineering programs should focus on, and argue that an industrial engineer is a decision maker instead of a problem solver.

Keywords: decision analysis, problem-solving, value creation, industrial engineering

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

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Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Arun Kumar, Neelesh Haulder

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This paper identifies and resolves some key issues relating to a specific aspect within the supply chain logistics of the public health care industry in the Republic of Mauritius. The analysis and the proposed solution are performed using soft systems methodology (SSM). Through the application of this relevant systematic approach at problem solving, the aim is to obtain an in-depth analysis of the problem, incorporating every possible world view of the problem and consequently to obtain a well explored solution aimed at implementing relevant changes within the current supply chain logistics of the health care industry, with the purpose of tackling the key identified issues.

Keywords: soft systems methodology, CATWOE, healthcare, logistics

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Authors: Yildiray Keskin, Omer Acan, Murat Akkus

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In this paper, the solution of fractional diffusion equations is presented by means of the reduced differential transform method. Fractional partial differential equations have special importance in engineering and sciences. Application of reduced differential transform method to this problem shows the rapid convergence of the sequence constructed by this method to the exact solution. The numerical results show that the approach is easy to implement and accurate when applied to fractional diffusion equations. The method introduces a promising tool for solving many fractional partial differential equations.

Keywords: fractional diffusion equations, Caputo fractional derivative, reduced differential transform method, partial

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Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

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Authors: Luis Javier Serrano-Tamayo

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This paper focuses on the recent interest in the concept of inclusion from multiple areas of social sciences, but particularly from the academic studies on what do scholars mean when they refer to inclusive education. Therefore, this paper has been based on a three-year systematic review of near two hundred peer-reviewed documents in the last two decades. The results illustrate some of the use, misuse, and abuse of inclusive education as well as shed some light on the identification of the different stakeholders involved in the dynamic concept of inclusive education and their suggested practices.

Keywords: inclusion, inclusive education, inclusive practices, education stakeholders

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: mathematics, motivation, secondary school, student, practical problem

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Authors: Hayle Makda Gebru

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Companies are inevitable for society. They are the building blocks of every development in a country aimed at producing continuous goods and services for the people and, in turn, obliged to pay taxes, which enhances the economy of the nation. For the proper functioning of companies, their relationship with their stakeholders must be secure. The major stakeholders are suppliers, consumers, employees, creditors, etc. The law plays an important role in enhancing the relationship between these different stakeholders. If the law fails to keep track of the relationship, both the company and stakeholders remain unprotected. As a result, the potential benefits are prejudiced. This paper makes a comparative analysis of the types and formation of companies under the Transitional Commercial Code of Eritrea and the Company Law of the Peoples Republic of China. In particular, the paper addresses the legal lacuna under the TCrCE on handling the failure of shareholders to pay the promised capital. So, the methodology of the study is entirely analyzing the two countries' laws using practical cases. After analyzing the practical problems on the ground using real cases, this paper calls on Eritrea to update its outdated Commercial Code to give proper protection to the stakeholders.

Keywords: companies, company law of the People's Republic of China, transitional commercial code of Eritrea, protection of stakeholders, failure to pay the promised capital

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Authors: Hitham Yami

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This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: Mustafa Ekici

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Natural convection is a basic process which is important in a wide variety of practical applications. In essence, a heated fluid expands and rises from buoyancy due to decreased density. Numerous papers have been written on natural or mixed convection in vertical ducts heated on the side. These equations have been proved to be valuable tools for the modelling of many phenomena such as fluid dynamics. Finding solutions to such equations or system of equations are in general not an easy task. We propose a method, which is called differential transform method, of solving a non-linear equations and compare the results with some of the other techniques. Illustrative examples shows that the results are in good agreement.

Keywords: differential transform method, momentum, energy equation, boundry value problem

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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Authors: M. Babul Hasan

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Management sciences (MS), big group of companies and industries or government policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. After formulating these models there arises large-scale mixed integer programming (MIP) problem. In this paper, we developed decomposition-based pricing procedure to filter the unnecessary decision ingredients from MIP where the variables in huge number will be abated and the complicacy of restrictions will be elementary. A real life numerical example has been illustrated to demonstrate the methods. We develop the computer techniques for these methods by using a mathematical programming language (AMPL).

Keywords: Lagrangian relaxation, decomposition, sub-problem, master-problem, pricing, mixed IP, AMPL

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Authors: A. Anis, W. Bekheet, A. El Hakim

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Implementing a Road Safety Management System (SMS) in a crowded developing country such as Egypt is a necessity. Beginning a sustainable SMS requires a comprehensive reliable data system for all information pertinent to road crashes. In this paper, a survey for the available data in Egypt and validating it for using in an SMS in Egypt. The research provides some missing data, and refer to the unavailable data in Egypt, looking forward to the contribution of the scientific society, the authorities, and the public in solving the problem of missing or unreliable crash data. The required data for implementing an SMS in Egypt are divided into three categories; the first is available data such as fatality and injury rates and it is proven in this research that it may be inconsistent and unreliable, the second category of data is not available, but it may be estimated, an example of estimating vehicle cost is available in this research, the third is not available and can be measured case by case such as the functional and geometric properties of a facility. Some inquiries are provided in this research for the scientific society, such as how to improve the links among stakeholders of road safety in order to obtain a consistent, non-biased, and reliable data system.

Keywords: road safety management system, road crash, road fatality, road injury

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Authors: C. F. Popoola, K. Akinsanya, S. B. Babarinde, D. A. Farinde

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This study investigated published financial statement as correlate of investment decision among commercial bank stakeholders in Nigeria. A correlation research design was used in the study. 180 users of published financial statement were purposively sampled from Lagos and Ibadan. Data generated were analyzed using Pearson correlation and regression. The findings of the study revealed that, balance sheet is negatively related with investment decision (r=-.483; p < .01) while income statement (r= .249; p < .001), notes on the account (r= .230; p < .001), cash flow statement (r= .202; p < .001), value added statement (r= .328; p < .001) and five-year financial summary (r= .191 ;p < .01) are positively related with investment decision. Findings also revealed that components of published financial statement significantly predicted good investment decision (R2= .983; F(5,175)=284.5; p < .05) for commercial bank stakeholders. Therefore, it was suggested that Nigeria banks and professional bodies should instigate programs that will increase the knowledge of stakeholders on published financial statement.

Keywords: commercial banks, financial statement, income statement, investment decision, stakeholders

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Authors: Samual Ayeni, A. S. Akinbani

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At present when the price of petroleum is going down beyond bearable level, there is a need to diversify the economy towards arable crop production since Nigeria is an agrarian country. Yam plays prominent role in solving the problem of hunger in Nigeria. There is scarcity of information on the effect of fertilizers in increasing the yield of yam and maintaining soil properties in South Western Nigeria. This study was therefore set up to determine fertilizer effect on properties and yield of yam. The experiment was conducted at Adeyemi College of Education Teaching and Research Farm to compare the effect of organic, Organomineral and mineral fertilizers on yield of yam. Ten treatments were used 10t/ha Wood Ash, 10t/ha Cattle Dung, 10t/ha Poultry Manure, 10t/ha Manufactured Organic, 10t/ha Organomineral Fertilizer, 400kg/ha NPK, 400kg/ha SSP, 400kg/ha Urea and control with treatment. The treatments were laid out in a Randomized Complete Block Design (RCBD) and replicated three times. Compared with control, Organomineral fertilizer significantly (P < 0.05) increased the soil moisture content, poultry manure, wood ash significantly decreased (< 0.05) the bulk density. Application of 10t/ha Organomineral fertilizer recorded the highest increase in the yield of yam among the treatments.

Keywords: organomineral fertilizer, organic fertilizer, SSP, bulk density

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Authors: M. Khaing, A. V. Tkacheva

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The work is devoted to solving the problem of temperature stresses, caused by the heating point of the round plate. The plate is made of elastoplastic material, so the Prandtl-Reis model is used. A piecewise-linear condition of the Ishlinsky-Ivlev flow is taken as the loading surface, in which the yield stress depends on the temperature. Piecewise-linear conditions (Treska or Ishlinsky-Ivlev), in contrast to the Mises condition, make it possible to obtain solutions of the equilibrium equation in an analytical form. In the problem under consideration, using the conditions of Tresca, it is impossible to obtain a solution. This is due to the fact that the equation of equilibrium ceases to be satisfied when the two Tresca conditions are fulfilled at once. Using the conditions of plastic flow Ishlinsky-Ivlev allows one to solve the problem. At the same time, there are also no solutions on the edge of the Ishlinsky-Ivlev hexagon in the plane-stressed state. Therefore, the authors of the article propose to jump from the edge to the edge of the mine edge, which gives an opportunity to obtain an analytical solution. At the same time, there is also no solution on the edge of the Ishlinsky-Ivlev hexagon in a plane stressed state; therefore, in this paper, the authors of the article propose to jump from the side to the side of the mine edge, which gives an opportunity to receive an analytical solution. The paper compares solutions of the problem of plate thermal deformation. One of the solutions was obtained under the condition that the elastic moduli (Young's modulus, Poisson's ratio) which depend on temperature. The yield point is assumed to be parabolically temperature dependent. The main results of the comparisons are that the region of irreversible deformation is larger in the calculations obtained for solving the problem with constant elastic moduli. There is no repeated plastic flow in the solution of the problem with elastic moduli depending on temperature. The absolute value of the irreversible deformations is higher for the solution of the problem in which the elastic moduli are constant; there are also insignificant differences in the distribution of the residual stresses.

Keywords: temperature stresses, elasticity, plasticity, Ishlinsky-Ivlev condition, plate, annular heating, elastic moduli

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Authors: Eugene Stepanov, Arcady Ponosov

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To model gene regulatory networks one uses ordinary differential equations with switching nonlinearities, where the initial value problem is known to be well-posed if the trajectories cross the discontinuities transversally. Otherwise, the initial value problem is usually ill-posed, which lead to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid dynamical systems, rather than switched ones, to regularize the problem. 'Hybridization' of the switched system means that one attaches a dynamic discrete component ('automaton'), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness of the initial value problem making it well-posed. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. Several examples are provided in the presentation, which support the suggested analysis. The method can also be of interest in other applied fields, where differential equations contain switchings, e.g. in neural field models.

Keywords: hybrid dynamical systems, ill-posed problems, singular perturbation analysis, switching nonlinearities

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