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Particle Swarm Optimization to Design Ideotypes for Sustainable Fruit Production Systems

Author

Listed:
  • 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)

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.

Suggested Citation

  • Abdeslam Kadrani & Mohamed-Mahmoud Ould Sidi & Bénédicte Quilot-Turion & Michel Génard & Françoise Lescourret, 2012. "Particle Swarm Optimization to Design Ideotypes for Sustainable Fruit Production Systems," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 3(2), pages 1-19, April.
    • Handle: RePEc:igg:jsir00:v:3:y:2012:i:2:p:1-19
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