Optimal configuration of a green product supply chain with guaranteed service time and emission constraints

被引:66
|
作者
Hong, Zhaofu [1 ]
Dai, Wei [2 ]
Luh, Hsing [3 ]
Yang, Chenchen [4 ]
机构
[1] Lanzhou Univ, Sch Management, Lanzhou, Gansu, Peoples R China
[2] Zhejiang Univ, Sch Math Sci, Hangzhou, Zhejiang, Peoples R China
[3] Natl Chengchi Univ, Dept Math Sci, Taipei, Taiwan
[4] Hefei Univ Technol, Sch Econ, Hefei, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
OR in environment and climate change; Supply chain configuration; Guaranteed service time; Emission constraint; Sustainable supply chain management; NETWORK; DESIGN; MODEL;
D O I
10.1016/j.ejor.2017.09.046
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper studies a supply chain configuration (SCC) problem for a green product family in consideration of guaranteed service time and emission constraints. Several alternative options can be employed to implement the functions of each stage and safety inventory is adopted to satisfy stochastic demands. An SCC model is formulated to optimize the service time and option selection decisions to minimize the overall cost of the supply chain. The structural properties of the model are addressed and the problem is decomposed into two subproblems, namely, the service time decision problem and option selection problem. For the service time decision problem, the structural properties of the supply chain network is carefully studied, based on which a spanning tree-based algorithm (STA) is presented to solve the problem optimally. For the option selection problem that is proven to be NP-hard, a particle swarm optimization algorithm (PSO) is adopted to efficiently solve the problem. Consequently, a hybrid algorithm (STA+PSO) is developed to solve the SCC model. The numerical results show that the hybrid algorithm can efficiently and effectively solve the SCC model. The emission constraints on green products have significant effects on the supply chain cost and the emissions of the products; while the guaranteed service time also remarkably influences the supply chain configuration. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:663 / 677
页数:15
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