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A generic fuzzy approach for multi-objective optimization under uncertainty

Abstract : Multi-objective optimization under uncertainty has gained considerable attention in recent years due to its practical applications in real-life. Many studies have been conducted on this topic, but almost all of them transformed the problem into a mono-objective one or just neglected the effects of uncertainty on the outcomes. This paper addresses specific uncertain multi-objective problems in which uncertainty is expressed by means of triangular fuzzy numbers. To handle these problems, we introduced a new approach able to solve them without any transformation by considering fuzziness propagation to the objective functions. The proposed approach is composed of two main contributions: First, a fuzzy Pareto dominance is defined for ranking the generated fuzzy solutions. Second, a generic fuzzy extension of well-known evolutionary algorithms is suggested as resolution methods. An experimental study on multi-objective Vehicle Routing Problems (VRP) with uncertain demands is finally carried to evaluate our approach.
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https://hal.inria.fr/hal-01942402
Contributor : Talbi El-Ghazali <>
Submitted on : Monday, December 3, 2018 - 11:04:30 AM
Last modification on : Friday, December 11, 2020 - 6:44:07 PM

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Oumayma Bahri, El-Ghazali Talbi, Nahla Ben Amor. A generic fuzzy approach for multi-objective optimization under uncertainty. Swarm and Evolutionary Computation, Elsevier, 2018, 40, pp.166-183. ⟨10.1016/j.swevo.2018.02.002⟩. ⟨hal-01942402⟩

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