Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises. (April 2017)

• Record Type: Journal Article
• Authors: Guo, Jianquan; Wang, Xinyue; Fan, Siyuan; Gen, Mitsuo
• Is Part Of: Computers & industrial engineering. Volume 106(2017)
• Page Start: 351
• Page End: 360
• Publication Date: 2017-04
• Subjects: Location and route planning -- Fresh food e-commerce enterprises -- Low-carbon -- Logistics network -- Genetic algorithm -- Particle swarm optimization algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.02.002
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A logistics network model under the environment of low-carbon is proposed. Solution processes with PSO and GA are constructed. The validity and reliability of the model are verified by a calculating case study. Provides a reference for the design of forward and reverse logistics network. Abstract: In view of the rapid development of low-carbon economy, the increasing distribution demand and returned demand which caused by the short shelf life and spoilage of fresh food, network and route planning model of a two-stage forward/reverse logistics is firstly proposed for fresh food e-commerce enterprises under the environment of low-carbon emissions (The objective in the first stage is to minimize the overall cost of the system, and the minimum overall cost of the circulation-type distribution vehicles routing is considered in the second stage). And the validity of the model is verified by adopting genetic algorithm (GA) and particle swarm optimization (PSO) algorithm with the study of the fresh food e-commerce enterprises of Shanghai. Furthermore, a good reference can be provided to build the forward and reverse logistics network and optimal route planning model of fresh food e-commerce enterprises and reduce the carbon emissions during its operation process.