Abstract

With the development of e-commerce, competition among enterprises is becoming fiercer. Furthermore, environmental problems can no longer be ignored. To address these challenges, we devise a green closed loop supply chain (GCLSC) with uncertain demand. In the problem, two conflict objectives and recycling the used products are considered. To solve this problem, a mathematical model is formulated with the chance constraint, and the ϵ -constraint method is adapted to obtain the true Pareto front for small sized problems. For larger sized problems, the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective simulated annealing method (MOSA) are developed. Numerous computational experiments can help manufacturers make better production and sales plans to keep competitive advantage and protect the environment.

Highlights

  • The development of e-commerce has markedly improved the circulation of commodities, and consumers have more choices in their preference

  • We study the green closed loop supply chain (GCLSC) problem

  • Similar to E-commerce service, the GCLSC is divided into four parts including manufacture, first-class warehouse, second-class warehouse and customer point

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Summary

Introduction

The development of e-commerce has markedly improved the circulation of commodities, and consumers have more choices in their preference. Many companies will be gradually eliminated if they cannot effectively improve customer satisfaction (the quality of products, logistics speed, etc.) and cut their cost (production cost, operation cost, etc.) To address these challenges, many studies about the design of the supply chain were discussed over several decades. A few enterprises like Jingdong (a famous on-line shopping platform in China) have begun to recycle the used products for reproducing or reducing the waste to respond to the sustainable development strategy. Corresponding to this phenomenon in real life, some research works about green closed loop supply chain (GCLSC) have been conducted to address the challenges deriving from the environment and customers. R is formed by the total solutions obtained from the two heuristics

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