Decentralized Decision System for Closed-Loop Supply Chain: A Bi-Level Multi-Objective Risk-Based Robust Optimization Approach

•A decentralized Bi-level model is designed for a closed-loop supply chain.•The robust multi-objective bi-level model is compared with its single-level variant.•The deterministic models are compared with the robust models.•Cost, work damage, and job opportunity are linked to DMs risk averseness.•The...

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Veröffentlicht in:Computers & chemical engineering Jg. 154; S. 107472
Hauptverfasser: Golpîra, Hêriş, Javanmardan, Ahvan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.11.2021
Schlagworte:
Bi-level programming
Closed-loop supply chain
Conditional value at risk
Karush-Kuhn-Tucker conditions
Robust optimization
Robust optimization
Bi-level programming
Karush-Kuhn-Tucker conditions
Closed-loop supply chain
Conditional value at risk
ISSN:0098-1354, 1873-4375
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Zusammenfassung:•A decentralized Bi-level model is designed for a closed-loop supply chain.•The robust multi-objective bi-level model is compared with its single-level variant.•The deterministic models are compared with the robust models.•Cost, work damage, and job opportunity are linked to DMs risk averseness.•The DMs attitude toward risk is carefully considered in the model formulation. This paper proposes a novel risk-based robust mixed-integer linear programming to design a decentralized closed-loop supply chain. The model is formulated as an uncertain bi-level multi-objective programming with multiple suppliers, manufacturers, and distributors, as the leader, and recovery, recycling, and disposal centers as the follower. A Scenario-based Conditional Value-at-Risk is employed to capture the demand uncertainty. The Karush-Kuhn-Tucker approach, ε−constraint, and LP-metric are leveraged to deal with the complexity of the bi-level coordination, and the multi-objectivity of the leader and follower. The performance of the model is compared with the performance of the deterministic decentralized model and the corresponding multi-objective model designed for the centralized system in both the robust and deterministic modes. Results indicate better performance of robust approaches compared to deterministic approaches. The decentralized approach provides better performance for the cost-sensitive decision-maker, especially the optimistic one, and those who are sensitive to social parameters prefer the centralized approach.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2021.107472