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Robust two-stage optimization consensus models with uncertain costs
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DOI：10.1016/j.ejor.2024.04.020.png)
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In the consensus -reaching process (CRP), decision -makers (DMs) frequently encounter the dilemma of too much uncertain information, which can lead the actual decision to deviate from the optimal solution obtained by the currently used consensus models. To do this, we construct two robust two -stage optimization consensus models with uncertain costs and obtain their robust two -stage counterparts. We then apply a Benders decomposition algorithm to solve the resulting models. Finally, the experimental results show that the new models are better suited for uncertain contexts and could help DMs produce more reliable choices.
Keyword:
(S) group decisions and negotiations
Minimum cost consensus
Two-stage stochastic programming
Robust optimization
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
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Minimum cost consensus modelling under various linear uncertain-constrained scenarios各种线性不确定约束场景下的最小成本共识建模.png)
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