Local Search with P Systems

Local search is currently one of the most used methods for finding solutions in real-life problems. It is usually considered when the research is interested in the final solution of the problem instead of the how the solution is reached. In this paper, the authors present an implementation of local search with Membrane Computing techniques applied to the N-queens problem as a case study. A CLIPS program inspired in the Membrane Computing design has been implemented and several experiments have been performed. The obtained results show better average times than those obtained with other Membrane Computing implementations that solve the N-queens problem

Particle Swarm Optimization to Design Ideotypes for Sustainable Fruit Production Systems

International audienceDesigning 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