A scenario-based stochastic programming approach for the product configuration problem under uncertainties and carbon emission regulations. (July 2018)

• Record Type: Journal Article
• Authors: Li, Xiaohong; Yang, Dong; Hu, Mengqi
• Is Part Of: Transportation research. Volume 115(2018)
• Page Start: 126
• Page End: 146
• Publication Date: 2018-07
• Subjects: Product configuration -- Stochastic programming -- Benders decomposition algorithm -- Carbon emission; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2018.04.013
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: Stochastic programming approach is employed to formulate product configuration problem. Benders decomposition is proposed to solve stochastic mixed-integer programming model. Computational results demonstrate the efficiency of suggested method. Analysis on impacts of emission regulations on configuration decisions are carried out. Abstract: To handle the product configuration problem with uncertain supply and demand, stochastic programming approach is applied to formulate the problem as a stochastic mixed-integer programming model. Carbon emission is further integrated into the deployed stochastic model under four different carbon emission regulations. Benders decomposition algorithm is utilized to solve the stochastic model. Computational studies show that the Benders decomposition method can solve large-scale stochastic programming problems with faster convergence rate than commercial solver CPLEX does. The results from the numerical experimental analysis demonstrate the impacts of carbon emission regulations on product configuration decisions.