A new Particle Swarm Optimization algorithm to solve multiobjective optimization problems is presented. After an initial search, the swarm is subdivided in a number of sub-swarms depending on the distance of each individual from the Pareto frontier. Effectiveness and efficiency of the proposed approach are preliminary investigated by solving a set of well- known test problems, and comparing the results with other evolutionary algorithms. Finally its usefulness is demonstrated in the multiobjective design of a containership.
A Particle Swarm Optimization Algorithm for Multiobjective Design Problems
2005
Abstract
A new Particle Swarm Optimization algorithm to solve multiobjective optimization problems is presented. After an initial search, the swarm is subdivided in a number of sub-swarms depending on the distance of each individual from the Pareto frontier. Effectiveness and efficiency of the proposed approach are preliminary investigated by solving a set of well- known test problems, and comparing the results with other evolutionary algorithms. Finally its usefulness is demonstrated in the multiobjective design of a containership.File in questo prodotto:
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