A Mathematical Programming Model with Equilibrium Constraints for Competitive Closed-Loop Supply Chain Network Design

Yuxiang Yang, Zuqing Huang (), Qiang Patrick Qiang () and Gengui Zhou ()
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Yuxiang Yang: College of Economics and Management, China Jiliang University, Hangzhou, Zhejiang 310018, P. R. China
Zuqing Huang: College of Economics and Management, China Jiliang University, Hangzhou, Zhejiang 310018, P. R. China
Qiang Patrick Qiang: Great Valley School of Graduate Professional Studies, Pennsylvania State University, Malvern, PA 19355, USA
Gengui Zhou: School of Business Administration, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2017, vol. 34, issue 05, 1-31

Abstract: A firm sets up his facilities including manufacturing/remanufacturing plants and distribution/collection centers, incorporating an existing closed-loop supply chain (CLSC) network. The entering firm has to compete with the existing firms in the existing network. The entering firm behaves as the leader of a Stackelberg game while the existing firms in the existing network are followers. We assume that the entering firm can anticipate the existing firms’ reaction to his potential location decision before choosing his optimal policy. We use a CLSC network equilibrium model in which the decision makers are faced with multiple objectives to capture the existing firms’ reaction. A mathematical programming model with equilibrium constraints is developed for this competitive CLSC network design problem by taking into account the market competition existing in the decentralized CLSC network. A solution method is developed by integrating Genetic algorithm with an inexact logarithmic-quadratic proximal augmented Lagrangian method. Finally, numerical examples and the related results are studied for illustration purpose.

Keywords: Closed-loop supply chain; competitive network design; Stackelberg game; variational inequalities (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0217595917500269

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