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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者单位:University of Regina
学位级别:博士
导师姓名:Rene V. Mayorga
授予年度:2018年
主 题:Closed Loop Supply Chain Sustainability Uncertainty Fuzzy Multi-objective Evolutionary Algorithms
摘 要:Sustainable Closed Loop Supply Chain (CLSC) management is increasingly adopted by companies, due to increasing concerns for the environmental, legislative compliance, decreasing availability of raw materials, and customer demands for environmentally friendly products. Sustainable CLSC network design provides a platform which ensures an effective and efficient supply chain management. In this thesis, the sustainable CLSC network design problem was formulated deterministically via Mixed Integer Linear Programming (MILP), and non- deterministically via Fuzzy Multi-objective Mixed Integer Linear Programming (FMOMILP) model, by considering sustainability and uncertainty. Fuzzy programming approaches were utilized to solve the problem. Two multi-objective evolutionary algorithms were employed to find the optimal solutions for large cases. Computational experiments were conducted, as well as studying actual industrial cases, to illustrate the applicability and significance of the proposed approaches and solution methods. Results showed that the Fuzzy Programming approach presents a systematic framework that enables management to obtain a satisfactory solution by adjusting the search direction. The results also demonstrated that the adopted Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is a satisfactory technique to solve large scale sustainable CLSC network design problems.