Dynamic joint construction and optimal operation strategy of multi-period reverse logistics network: a case study of Shanghai apparel E-commerce enterprises

Jianquan Guo (), Xinxin Liu and Jungbok Jo
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Jianquan Guo: Business School of University of Shanghai for Science and Technology
Xinxin Liu: Business School of University of Shanghai for Science and Technology
Jungbok Jo: Dongseo University

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 3, No 33, 819-831

Abstract: Abstract With the rapid development of our economy, the demand for reverse logistics is becoming increasingly urgent. This paper proposes a multi-period and dynamic joint construction model to build the reverse logistics network and verifies the feasibility of the rendered model by adopting particle swarm optimization (PSO) algorithm and genetic algorithm (GA) with a case study of the apparel E-commerce enterprises of Shanghai. The calculation indicates that, compared with traditional single-period reverse logistics system, dynamic joint construction model is more accordant with the practical situation, the capacity of multi-period model node is easier to optimize and the total operation cost of multi-period model reduces a lot. Furthermore, this research provides reference for reducing the operation costs as well as the building of regional reverse logistics network.

Keywords: Reverse logistics; Multi-period network; Dynamic joint construction; Apparel E-commerce enterprises; Particle swarm optimization (PSO) and genetic algorithm (GA) (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10845-015-1034-8

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