A leader-follower approach for hazmat closed loop supply chain network design

نوع: Type: thesis

مقطع: Segment: Masters

عنوان: Title: A leader-follower approach for hazmat closed loop supply chain network design

ارائه دهنده: Provider: Vahid Shabani

اساتید راهنما: Supervisors: Dr. Amirsaman Kheirkhah

اساتید مشاور: Advisory Professors: Dr. Masoume Messi Bidgoli

اساتید ممتحن یا داور: Examining professors or referees: Dr. Vahid Khodakarami, Dr. Parvaneh Samouei

زمان و تاریخ ارائه: Time and date of presentation: Wednesday 22/September/2021

مکان ارائه: Place of presentation: Virtual class

چکیده: Abstract: On the grounds of increasing environmental concerns, human hazards, government regulations, and awareness of natural resource constraints, the closed-loop supply chain network design has attracted the attention of many researchers. The reluctance of companies to perform reverse activities along with forward activities is due to high costs as well as uncertainty in the quality and quantity of returned products, which raises environmental concerns, human hazards and contribute to become one of the most important challenges of governments today. In this research, a two-level mixed integer programming model is proposed. At the first level, the government, as a leader, seeks to minimize the risk associated with the presence of dangerous goods in these centers and the routes leading to them, by identifying the locations for distribution and collection centers, with the aim of reducing environmental pollution caused by the presence of dangerous goods in the network. It also seeks to guarantee a certain proportion of each customer's demand. At the second level, the private sector, according to government decisions, seeks to determine the amount of goods flowing within the network, and designs its closed-loop supply chain network optimally with the aim of minimizing its costs. In order to solve the proposed model, it validates the validity of the model based on the method of complete counting of the obtained values. Then, due to the NP-hard nature of the problem, the Shuffling Frog Leaping Algorithm (SFLA) is used to solve it in large dimensions, and its performance results are compared with the Genetic Algorithm (GA). The results show that the proposed algorithm (SFL) has performed well in solving such problems.

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