Green supply chain planning considering consumer's transportation process. (January 2018)

• Record Type: Journal Article
• Authors: Gao, Jingzhe; Xiao, Zhongdong; Cao, Binbin; Chai, Qiangfei
• Is Part Of: Transportation research. Volume 109(2018)
• Page Start: 311
• Page End: 330
• Publication Date: 2018-01
• Subjects: Carbon cap -- Mixed-integer nonlinear programming -- Supply chain network design -- Green supply chain planning; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2017.12.001
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: Considering carbon emissions from both firms and consumers. Solving optimal delivery volume, inventory and store density. Designing a two-step method to get the exact solutions of the MINLP models. Studying the impact of the density of stores on the cost and carbon emissions. Providing basis for supply chain assignment and store establishment decisions. Providing guidance for firms to improve the attractiveness to consumers. Providing a reference for the government in designing carbon emission policy. Abstract: This article addresses a product delivery and store network layout strategy problem considering not only firms' but also consumers' cost. The study presents several mathematical programming models to minimize the cost or maximize the profit. Then, we design a two-step solution method for exact solutions and present an implementation. The results show that a carbon cap will do more good than harm for the environment. Trying to minimize the cost from both sides will not only improve the efficiency of social resource use but also enable stores to attract more consumers. Limiting emissions for firms will result in significant emissions reduction without an excessive cost increase.