2020/11/20 by El‐Ghazali Talbi, Talbi, El-Ghazali, Raca Todosijević +1
Decision Sciences · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Mathematical Programming #Process Optimization and Integration #Risk and Portfolio Optimization
paper · pdf · doi:10.48550/arxiv.2011.10341
openalex publication_date 2020/11/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents a new robustness concept for uncertain multi-objective optimization problems. More precisely, in the paper the so-called recovery-to-efficiency robustness concept is proposed and investigated. Several approaches for generating recovery-to-efficiency robust sets in the context of multi-objective optimization are proposed as well. An extensive experimental analysis is performed to disclose differences among robust sets obtained using different concepts as well as to deduce some interesting observations. For testing purposes, instances from the bi-objective knapsack problem are considered.