ale-pso an adaptive swarm algorithm to solve design problems of laminatesale-pso分层的自适应蜂群算法来解决设计问题.pdfVIP

Algorithms 2009, 2, 710-734; doi:10.3390/a2020710 OPEN ACCESS algorithms ISSN 1999-4893 /journal/algorithms Article ALE-PSO: An Adaptive Swarm Algorithm to Solve Design Problems of Laminates Paolo Vannucci Institut Jean Le Rond dAlembert – UMR CNRS 7190, Tour 55-65, Case 161 – 4, Place Jussieu, 75252 Paris Cedex 05 – France; E-mail: vannucci@lmm.jussieu.fr * Author to whom correspondence should be addressed. Received: 23 March 2009; in revised version: 13 April 2009 / Accepted: 16 April 2009 / Published: 21 April 2009 Abstract. This paper presents an adaptive PSO algorithm whose numerical parameters can be updated following a scheduled protocol respecting some known criteria of convergence in order to enhance the chances to reach the global optimum of a hard combinatorial optimization problem, such those encountered in global optimization problems of composite laminates. Some examples concerning hard design problems are provided, showing the effectiveness of the approach. Keywords. Laminates, polar method, global optimization, swarm intelligence, parameters tuning. 1. Introduction The Particle Swarm Optimization method (PSO) is a metaheuristic introduced by Eberhart and Kennedy [1] to solve complex optimization problems. It inspired by and it mimics in an algebraic way the social behaviour and dynamics of groups of individuals (particles), such as the flocks of birds, whose groups