Optimizing Product Configuration Problems with Multisourcing Supplier Selections under Both Carbon Cap and Carbon Tax Regulations

被引:3
|
作者
Li, Jia [1 ]
Yang, Dong [1 ]
机构
[1] Donghua Univ, Sch Business & Management, Shanghai 200051, Peoples R China
关键词
OF-THE-ART; MASS CUSTOMIZATION; CUSTOMER SATISFACTION; GENETIC ALGORITHM; FAMILY DESIGN; OPTIMIZATION; IDENTIFICATION; REQUIREMENTS; TAXATION; SYSTEM;
D O I
10.1155/2022/6298982
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Product configuration is a key enabling technology for mass customization production. Previous studies mainly focus on the solving technologies for obtaining a feasible configuration or optimal configuration but ignore environmental factors like CO2 emissions, especially the environmental regulations from international organizations. In this article, we address product configuration optimization problems considering both carbon cap and carbon tax regulations. A two-stage approach that combines both Particle Swarm Optimization (PSO) and a greedy algorithm is presented to solve the product configuration problems with carbon emission concerns. A case study of a configurable ranger-drilling machine is illustrated to demonstrate the effectiveness of the presented approach. The impacts of carbon cap and carbon tax regulations on configuration results are compared. Further, the models are extended to analyze the effects of single-sourcing and multisourcing on product configuration. The analysis shows that multisourcing in combination with carbon tax regulation can facilitate a manufacturer to provide more green and low-carbon customized products for customers. Numerical experiments are conducted to validate the effectiveness of the model and the efficiency of the proposed solution method.
引用
收藏
页数:16
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