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.
| Original language | English (US) |
|---|---|
| Article number | 1750026 |
| Journal | Asia-Pacific Journal of Operational Research |
| Volume | 34 |
| Issue number | 5 |
| DOIs | |
| State | Published - Oct 1 2017 |
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All Science Journal Classification (ASJC) codes
- Management Science and Operations Research
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A Mathematical Programming Model with Equilibrium Constraints for Competitive Closed-Loop Supply Chain Network Design. / Yang, Yuxiang; Huang, Zuqing; Qiang, Qiang; Zhou, Gengui.
In: Asia-Pacific Journal of Operational Research, Vol. 34, No. 5, 1750026, 01.10.2017.Research output: Contribution to journal › Article
TY - JOUR
T1 - A Mathematical Programming Model with Equilibrium Constraints for Competitive Closed-Loop Supply Chain Network Design
AU - Yang, Yuxiang
AU - Huang, Zuqing
AU - Qiang, Qiang
AU - Zhou, Gengui
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
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U2 - 10.1142/S0217595917500269
DO - 10.1142/S0217595917500269
M3 - Article
AN - SCOPUS:85029545459
VL - 34
JO - Asia-Pacific Journal of Operational Research
JF - Asia-Pacific Journal of Operational Research
SN - 0217-5959
IS - 5
M1 - 1750026
ER -