A robust possibilistic programming framework for designing an organ transplant supply chain under uncertainty

DOI10.1007/s10479-022-04829-7OpenAlexW4288695994WikidataQ114227561 ScholiaQ114227561MaRDI QIDQ6179182

SeyedAli Mirjalili, Ali Ala, Alireza Goli

Publication date: 5 September 2023

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-022-04829-7

zbMATH Keywords

simulation-based optimizationfuzzy uncertaintyrobust possibilistic programminghealthcare operationsorgan transplantation

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Fuzzy and other nonstochastic uncertainty mathematical programming (90C70) Robustness in mathematical programming (90C17)

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Cites Work

• Robust possibilistic programming for socially responsible supply chain network design: a new approach
• Linear programming with fuzzy parameters: an interactive method resolution
• Fuzzy sets as a basis for a theory of possibility
• A network model for minimizing the total organ transplant costs
• Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge
• Possibilistic linear programming: A brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem
• Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec
• Optimizing Organ Allocation and Acceptance
• Maximizing the Efficiency of the U.S. Liver Allocation System Through Region Design
• A Broader View of Designing the Liver Allocation System
• A multi-objective robust possibilistic programming approach to sustainable public transportation network design

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