Module-Based Product Configuration Decisions Considering Both Economical and Carbon Emission-Related Environmental Factors

Abstract

With an increasing demand for green and environmentally friendly products, configuring a customized product from modular product design to satisfy both individualized customer requirements and environment restrictions has become a vital task for mass customization. In this paper, we addressed a module-based product configuration problem under carbon emission regulation, i.e., carbon cap-and-trade schema. The configuration problem under carbon cap-and-trade schema was formulated as a mixed-integer programming problem. Due to the NP-hard characteristics of the model, a genetic algorithm was employed to solve the configuration problems under carbon cap-and-trade. Experiments were carried out to analyze the effects of carbon emissions on product configuration decisions and carbon purchasing decisions. As a result, the range for carbon emission cap is suggested for both manufacturers and government agency, which provides the decision supporting for both customized and low-carbon production and green manufacturing.