An adaptable robust optimization model for a dual-channel closed-loop supply chain considering cost and demand uncertainty

Kaoud, Essam; Abdel-Aal, Mohammad A. M.; SAKAGUCHI, Tatsuhiko; Uchiyama, Naoki

doi:10.1299/jamdsm.2022jamdsm0038

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…[26] analyzed the influence of manufacturers' or retailers' risk aversion preference on their late payment decisions and effectiveness when adopting dual-channel structure. [27] provided an adaptive robust optimization model for a two-channel closed-loop supply chain that considers cost and demand uncertainties. [28] developed a novel distributionally robust optimization modeling framework for the capital-constrained dual-channel supply chain.…”

Section: Literature Reviewmentioning

confidence: 99%

Channel Competition and Coordination of a Dual-Channel Supply Chain under Interval Demand

2023

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Interval demand is becoming more common than ever before, since the variation bounds of uncertain demand are only required in practice, and they could be obtained through only a small amount of uncertain information. The goal of this paper is to analyze the optimal decision and coordination of a competitive dual-channel supply chain under an interval uncertain demand. For this purpose, we establish a centralized decision model and a wholesale price contract model under both interval demand and channel competition, respectively. Meanwhile, both the satisfaction degree of interval and the order relation of interval number are proposed to convert interval uncertain optimization problems to deterministic ones. Then, we derive the optimal pricing decisions, ordering quantities, and performances of partners and the supply chain system. Meanwhile, a revenue sharing contract is proposed to coordinate the competitive dual-channel supply chain under interval demand. Moreover, we found that the bounds of interval demand and channel sensitivities affect the optimal strategies and revenue sharing contract under interval uncertainty. Finally, we present a numerical analysis to illustrate the proposed results in this paper and conduct sensitivity analyses. The findings of this paper provide important references for decision makers and managers to make scientific decisions in an interval uncertain environment.

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Section: Literature Reviewmentioning

confidence: 99%

Channel Competition and Coordination of a Dual-Channel Supply Chain under Interval Demand

2023

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Robust optimization model for traceable procurement of construction materials considering contract claims

Zhang,

Zhou,

Ning

et al. 2024

Automation in Construction

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Operation Optimization of Wastewater Treatment Process Based on Robust Subgroup Information Synergy Strategy

Cui,

Tian,

Xie

et al. 2024

Water

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In order to address the issues of system fluctuation and low efficiency brought on by various disturbance factors in wastewater treatment plants (WWTPs), this study builds a robust multi-objective optimization model and determines the ideal parameters for enhancing the robustness and stability of energy consumption (EC) and effluent quality (EQ). Firstly, a novel robust index is proposed, merging the signal-to-noise ratio and standard deviation., comprehensively considering data volatility and anti-interference capability to guide the establishment of a robust optimization model. Secondly, considering the energy consumption errors and water quality data measurement caused by noise factors, which increases the difficulty and time complexity of the solution. Therefore, this paper uses a multi-objective mantis search algorithm (MOMSA) based on a robust subgroup, and an information synergy strategy is used to solve the problem. The strategy first divides the population into strong and weak robust subgroups according to their robustness. Then, the co-evolutionary strategy and the information enhancement strategy will be used to guide the evolutionary direction of the individual from the whole and the local perspectives, thereby comprehensively improving the convergence speed of the algorithm. Based on the test function, this shows that the convergence, diversity, and comprehensive performance of the improved algorithm are better than other algorithms. Experimental results based on the BSM1 platform show that the improved algorithm is effective in finding robust solutions with strong stability despite changes in external factors (e.g., precipitation). According to the experimental results based on real industrial problems, the new robustness metrics can effectively evaluate the robustness of the optimization model, and compared with other algorithms, the algorithm proposed in this paper yields solutions of more reliable quality and faster convergence performance, which can successfully solve the robust optimization problem in wastewater treatment plants.

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An adaptable robust optimization model for a dual-channel closed-loop supply chain considering cost and demand uncertainty

Cited by 3 publications

References 29 publications

Channel Competition and Coordination of a Dual-Channel Supply Chain under Interval Demand

Channel Competition and Coordination of a Dual-Channel Supply Chain under Interval Demand

Robust optimization model for traceable procurement of construction materials considering contract claims

Operation Optimization of Wastewater Treatment Process Based on Robust Subgroup Information Synergy Strategy

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