A chance-constraint optimization model for a multi-echelon multi-product closed-loop supply chain considering brand diversity: an accelerated Benders decomposition algorithm

DOI10.1016/j.cor.2022.106130OpenAlexW4313334221MaRDI QIDQ6109344

Meysam Borajee, Seyed-Houman Madani-Saatchi, Reza Tavakkoli-Moghaddam

Publication date: 4 July 2023

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2022.106130

zbMATH Keywords

uncertaintymixed-integer linear programmingclosed-loop supply chainaccelerated benders decompositionchance-constraint optimization

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

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• Robust supply chain network design with service level against disruptions and demand uncertainties: a real-life case
• Exact algorithms based on Benders decomposition for multicommodity uncapacitated fixed-charge network design
• A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks
• A Benders' decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato
• An improved Benders decomposition algorithm for the logistics facility location problem with capacity expansions
• Competitive facility location problem with foresight considering discrete-nature attractiveness for facilities: model and solution

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