Research on closed-loop supply chain network equilibrium with two-type suppliers, risk-averse manufacturers and capacity constraints

Hao Sun, Li Jian, Guitao Zhang


Purpose: the aim of this paper is to investigate the closed-loop supply chain (CLSC) network equilibrium wiht the consideration of three practical factors: two complementary types of suppliers, risk-averse character of the manufacturer and capacity constraints of the suppliers.

Design/methodology/approach: The equilibrium of various decision makers including the suppliers, the manufacturers, the retailers, the collectors and the demand markets are modeled via finite-dimensional variational inequality, respectively. Then the governing CLSC network equilibrium model is established. The logarithmic-quadratic proximal prediction-correction algorithm is designed to solve the variational inequality model. Numerical examples are given to analyze the impact of return rate, risk-averse degree and capacity constraints on the network equilibrium under different product BOMs.

Findings: with the increase of return rate, the profits of various channel members and the performance of the CLSC system will improve. There is a contradiction between profit maximization and risk minimization for the manufacturers. Moreover, the economic behavior of the CLSC is likely to be limited by the capacity constraints of the suppliers.

Originality/value: Prior to this paper, few papers have addressed with the CLSC network equilibrium considering some practical factors. They assume all the suppliers are identical and all the decision-makers are risk neutral. Furthermore, the production capacities of all suppliers are assumed to be infinite or large enough. To fill the gap, this paper examines the influences of two-type suppliers, risk aversion and capacity constraints upon the CLSC network equilibrium.


closed-loop supply chain network; variational inequalities; multi-type suppliers; risk averse; capacity constraints

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Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2024

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience