Recovery-to-Efficiency: A New Robustness Concept for Multi-objective Optimization under Uncertainty
This paper addresses the problem of defining and generating robust solutions for multi-objective optimization problems under uncertainty, which is relevant for decision-makers seeking reliable outcomes in complex scenarios.
This paper introduces a new robustness concept, 'recovery-to-efficiency,' for multi-objective optimization problems under uncertainty. It proposes several approaches for generating robust sets based on this concept and experimentally analyzes their differences using instances of the bi-objective knapsack problem.
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.