Bi-objective supply chain problem using MOPSO and NSGA-II

The increase competition and decline economy has increased the relevant importance of having reliable supply chain. The primary objective of many supply chain problems is to reduce the cost of services and, at the same time, to increase the quality of services. In this paper, we present a multi-level supply chain network by considering multi products, single resource and deterministic cost and demand. The proposed model of this paper is formulated as a mixed integer programming and we present two metaheuristics namely MOPSO and NSGA-II to solve the resulted problems. The performance of the proposed models of this paper has been examined using some randomly generated numbers and the results are discussed. The preliminary results indicate that while MOPSO is able to generate more Pareto solutions in relatively less amount of time, NSGA-II is capable of providing better quality results

Finding the Shortest Path in Dynamic Network using Labeling Algorithm

Abstract This study concerns the problem of finding shortest paths from one node to all other nodes in networks for which arc costs can vary with time, each arc has a transit time and parking with a corresponding time-varying cost is allowed at the nodes. it show that this problem is equivalent to a classical shortest path problem in a timeexpanded network. The label correcting algorithm is used for finding shortest paths. Keywords: Dynamic shortest paths, time-expanded network, label correcting algorithm. Introduction In congested transportation networks, arc travel times change over time due to time-of-day variations in traffic congestion. Even if one can account for these time-of-day variations, future travel times can at best be known a priori with uncertainty due to unforeseen events, such as poor roadway conditions, vehicle breakdowns, traffic accidents, and driver behavior. In this work, we develop path search techniques that explicitly consider the inherent time-varying nature of future travel times. Recent studies have focused on time-dependent graphs Review of the shortest path proble

Using Hybrid Fuzzy PROMETHEE II and Fuzzy Binary Goal Programming for Risk Ranking: A Case Study of Highway Construction Projects

Multi attribute decision making methods are considered as one of the most useful methods for solving ranking problems. In some decision making problems, while the alternatives for corresponding criteria are compared in a pairwise comparison manner, if the criteria are inherently fuzzy, debates will arise in ranking alternatives due to the closeness of the values of the criteria. In this research, the fuzzy PROMETHEE II is proposed as a solution in such conditions. First, using the ANP method, the criteria are weighted. Then, the ranking process is accomplished both by the fuzzy PROMETHEE II and the fuzzy TOPSIS methods. Finally, calculating Spearman correlation coefficient, the results of these two approaches are compared. Then, the most important risks are selected via the fuzzy binary goal programming and ranked again through the fuzzy PROMETHEE II and fuzzy TOPSIS methods finally, in the last step, these ranking two are compared. As a case study, highway construction risks are ranked through this method.</p

Evaluation of power plants to prioritise the investment projects using fuzzy PROMETHEE method

Increasing population growth of Iran, and consequently, increasing the annual energy consumption has made the construction of more than 3000 MW power plant necessary. Taking into account various criteria, some power plants have been evaluated and ranked to select the most appropriate power plant for investment. For this purpose, three aspects and seven main criteria for evaluating power plants have been determined. Afterward, weights of sub-criteria have been determined by Analytical Network Process method, and eventually, power plants have been ranked by a multi-criteria decision-making (MCDM) method (i.e. fuzzy PROMETHEE II). Moreover, a comprehensive sensitivity analysis has been carried. Finally, power plants have been ranked by fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method once again. Since the value of Spearman Correlation Test for two implemented methods is equal to 0.98, it can be concluded that fuzzy PROMETHEE II performs as well as fuzzy TOPSIS in ranking alternatives

An Improved Hybrid Grey Relational Analysis Approach for Green Resilient Supply Chain Network Assessment

In the growing and turbulent market of the current world both in national and in international relations, the need for reviewing and assessment of the resiliency of suppliers as one of the new concepts in supply chain management has been prioritized. In addition, globalization, increasing the regulations of governmental and non-governmental organizations, customers’ request and pressure regarding environmental issues has led organizations to evaluate the measures necessary to implement green supply chain management, to improve their environmental and economic performance. The subject of selecting and evaluating suppliers on green supply chain with resilience capability first requires the identification of the supplier evaluation criteria so that it considers the resiliency of the supply chain concurrent with the concepts of green supply chain. Secondly, right tools should be used for the decision. Considering all the criteria and indicators in conditions of uncertainty encourages the development and application of methods, such as fuzzy theory and grey systems theory. In this research, a comprehensive model for evaluating green resilience supply chain network is provided. In order to apply both quantitative and qualitative criteria, the possibility of making the target based criteria dimensionless along the cost or benefit criteria, the use of experts’ opinions in the allocation of weights to the criteria and indicators using grey numbers, grey relational analysis are developed and improved. In the end, the implementation of the proposed model is explained step by step in a case study and the future conclusions and recommendations are suggested