Particle Swarm Optimization to Design Ideotypes for Sustainable Fruit Production Systems

Abdeslam Kadrani, Mohamed-Mahmoud Ould Sidi, Bénédicte Quilot-Turion, Michel Génard and Françoise Lescourret
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Abdeslam Kadrani: INRA, UR1115 PSH, F-84000 Avignon, France
Mohamed-Mahmoud Ould Sidi: INRA, UR1115 PSH, F-84000 Avignon, France
Bénédicte Quilot-Turion: INRA, UR1115 PSH, F-84000 Avignon, France
Michel Génard: INRA, UR1115 PSH, F-84000 Avignon, France
Françoise Lescourret: INRA, UR1115 PSH, F-84000 Avignon, France

International Journal of Swarm Intelligence Research (IJSIR), 2012, vol. 3, issue 2, 1-19

Abstract: Designing peach ideotypes that satisfy the requirement of high fruit quality and low sensitivity to brown rot in a given environment was formulated as a multi-objective problem. The ‘Virtual Fruit’ model was used to perform virtual experiments. Particle swarm optimization (PSO) was interfaced to the ‘Virtual Fruit’ for solving the weighted optimization problem resulting by the linear aggregation of the criteria of the multi-objective problem. The comparison of the PSO with the Genetic Algorithm (GA) showed that the PSO method achieves better performance and outperforms the GA. The optimization results found by the PSO algorithm are considered to be satisfactory for the sustainable production systems of the peach fruit.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:3:y:2012:i:2:p:1-19

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