Fuzzy Random Weighted Weber Problems in Facility Location

This article considers facility location in a Weber problem with weights including both uncertainty and vagueness. By representing its weights as fuzzy random variables, it can be extended to a fuzzy random weighted Weber problem, and then formulated as a fuzzy random programming problem. By introducing possibility and necessity measures and chance constraints, the extended problem is reformulated to new two types of Weber problems. Based upon characteristics of facility location, theorem for solving the reformulated problems are shown

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

Suppliers Selection In Manufacturing Industries And Associated Multi-Objective Desicion Making Methods: Past, Present And The Future

Nowadays, many manufacturing companies have decided to use other companies’ competencies and outsource part of their manufacturing processes and business to suppliers globally in order to reduce costs, improve quality of products, explore or expand new markets, and offer better services to customers, etc. The decisions have rendered manufacturing organizations with new challenges. Organizations need to evaluate their suppliers' performance, and take account of their weakness and strength in order to win and survive in highly competitive global marketplaces. Hence, suppliers evaluation and selection are taken as an important strategy for manufactring enterprises. This paper aims to provide a comprehensive and critical review on suppliers selection and the formulation of different criteria for suppliers selection, the associated multi-objctive decision makings, selecion algorithms, and their implementation and application perspectives. Furthermore, individual and integrated suppliers selection approaches are presented, including Analytic hierarchy process (AHP), Analytic network process (ANP), and Mathematical programming (MP). Linear programming (LP), Integer programming (IP), Data envelopment analysis (DEA) and Goal programming (GP) are discussed with in-depth. The paper concludes with further discussion on the potential and application of suppliers selection approach for the broad manufacturing industry

Local Ideal Point Method for GIS-based Multicriteria Analysis: A Case Study in London, Ontario

GIS-based multicriteria analysis (GIS-MCA) is a procedure for transforming and combining geographic data and value judgments (preferences) to evaluate a set of alternatives with respect to relevant criteria. Ideal Point Method (IPM) is one of the most often used GIS-MCA techniques. It has been applied in many research/planning areas including environmental planning, urban/regional planning, waste management, water resource management and agriculture. One of the limitations of IPM is that it has conventionally been used as a global approach based on the implicit assumption that its parameters do not vary as a function of geographic space. The conventional IPM assumes a spatial homogeneity of its parameters within the whole study area. This thesis proposes a new IPM called local IPM. The local version of IPM is developed by localizing two parameters (criterion weights and ideal/nadir points) based on the range-sensitivity principle. The IPM methods are used to evaluate and analyse the spatial patterns of the quality of employment in London, Ontario. The case study shows that there are significant differences between the spatial patterns generated by the local and conventional IPM. The local IPM not only can display the general ‘spatial trend’ of the quality of employment in London, but also is able to highlight the areas with relatively high quality of employment in different neighborhoods. Furthermore, the local IPM provides a tool for visualizing and exploring spatial patterns. The parameters influencing the local IPM results can be mapped and further examined with GIS

An Allocation-Routing Optimization Model for Integrated Solid Waste Management

Integrated smart waste management (ISWM) is an innovative and technologically advanced approach to managing and collecting waste. It is based on the Internet of Things (IoT) technology, a network of interconnected devices that communicate and exchange data. The data collected from IoT devices helps municipalities to optimize their waste management operations. They can use the information to schedule waste collections more efficiently and plan their routes accordingly. In this study, we consider an ISWM framework for the collection, recycling, and recovery steps to improve the performance of the waste system. Since ISWM typically involves the collaboration of various stakeholders and is affected by different sources of uncertainty, a novel multi-objective model is proposed to maximize the probabilistic profit of the network while minimizing the total travel time and transportation costs. In the proposed model, the chance-constrained programming approach is applied to deal with the profit uncertainty gained from waste recycling and recovery activities. Furthermore, some of the most proficient multi-objective meta-heuristic algorithms are applied to address the complexity of the problem. For optimal adjustment of parameter values, the Taguchi parameter design method is utilized to improve the performance of the proposed optimization algorithm. Finally, the most reliable algorithm is determined based on the Best Worst Method (BWM)

Developing a meat supply chain network design using a multi-objective possibilistic programming approach

Purpose The purpose of this paper is to present a study in developing a cost-effective meat supply chain network design aiming to minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. The developed model was also used for determining the optimum numbers and allocations of farms and abattoirs that need to be established and the optimal quantity flow of livestock from farms to abattoirs and meat products from abattoirs to retailers. Design/methodology/approach A multi-objective possibilistic programming model was formulated with a focus on minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. Three sets of Pareto solutions were obtained using the three different solution methods. These methods are the LP-metrics method, the ɛ-constraint method and the weighted Tchebycheff method, respectively. The TOPSIS method was used for seeking a best Pareto solution as a trade-off decision when optimizing the three conflicting objectives. Findings A case study was also applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. The research concludes that the ɛ-constraint method has the superiority over the other two proposed methods as it offers a better solution outcome. Research limitations/implications This work addresses as interesting avenues for further research on exploring the delivery planner under different types of uncertainties and transportation means. Also, environmentalism has been increasingly becoming a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The developed design methodology can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value The paper presents a methodology that can be used for tackling a multi-objective optimization problem of a meat supply chain network design. The proposed optimization method has the potential in solving the similar issue providing a compromising solution due to conflicting objectives in which each needs to be achieved toward an optimum outcome to survive in the competitive sector of food supply chains network. </jats:sec