Wednesday 29
Optimization under uncertainty
M. Aider
› 11:10 - 11:30 (20min)
Optimization Algorithms for Multi-objective Combinatorial Problems under Uncertainty
Oumayma Bahri  1@  , Nahla Ben Amor  1, *@  , Talbi El-Ghazali  2, *@  
1 : LARODEC Laboratory
2 : INRIA Laboratory
Université Lille I - Sciences et technologies
* : Corresponding author

Multi-objective optimization under uncertainty is an important line of research that has seen a great interest in recent years. Our aim is to deal with multi-objective problems with fuzzy data expressed by means of triangular fuzzy numbers. As a consequence, the objective functions to be optimized in this case will be disrupted by the used fuzzy form. To this end, we first propose a new Pareto approach for ranking the generated triangular-valued functions. Then, based on the proposed approach, we introduce a fuzzy extension of two well-known multi-objective evolutionary algorithms: SPEA2 and NSGAII in order to enable them handling such problems. An application on a multi-objective vehicle routing problem with uncertain demands is finally performed and validated through an experimental study.

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