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The relationship between metaheuristics stopping criteria and performances: Cases of NSGA-II and MOPSO-CD for sustainable peach fruit design

Abstract : A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop computation. Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance. This paper addresses this issue using the Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Multi- Objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD) for the model-based design of sustainable peach fruits. The optimization problem of interest contains three objectives: maximize fruit fresh mass, maximize fruit sugar content, and minimize the crack density on the fruit skin. This last objective targets a reduction in the use of fungicides and can thus enhance preservation of the environment and human health. Two versions of the NSGA-II and two of the MOPSO-CD were applied to tackle this difficult optimization problem: the original versions with a maximum number of generations used as stopping criterion and modified versions using the stopping criterion proposed by the authors of (Roudenko & Schoenauer, 2004). This second stopping criterion is based on the stabilization of the maximal crowding distance and aims to stop computation when many generations are performed without further improvement in the quality of the solutions. A benchmark consisting of four plant management scenarios has been used to compare the performances of the original versions (OV) and the modified versions (MV) of the NSGA-II and the MOPSO-CD. Twelve independent simulations were performed for each version and for each scenario, and a high number
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https://hal.inrae.fr/hal-02637046
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Submitted on : Wednesday, May 27, 2020 - 10:02:37 PM
Last modification on : Tuesday, February 9, 2021 - 11:48:04 AM

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Mohamed Ould Sidi, Bénédicte Quilot-Turion, Abdeslam Kadrani, Michel Génard. The relationship between metaheuristics stopping criteria and performances: Cases of NSGA-II and MOPSO-CD for sustainable peach fruit design. International Journal of Applied Metaheuristic Computing, IGI Global Publisher, 2014, 5 (3), pp.47-74. ⟨10.4018/ijamc.2014070104⟩. ⟨hal-02637046⟩

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