Initial Particles Position for PSO,in Bound Constrained Optimization

摘要：

　　We consider the solution of bound constrained optimization problems, where we assume that the evaluation of the objective function is costly, its derivatives are unavailable and the use of exact derivative free algorithms may imply a too large computational burden.There is plenty of real applications, e.g.several design optimization problems 1,2,belonging to the latter class, where the objective function must be treated as a black-box and automatic differentiation turns to be unsuitable.Since the objective function is often obtained as the result of a simulation, it might be affected also by noise, so that the use of finite differences may be definitely harmful.In this paper we consider the use of the evolutionary Particle Swarm Optimization (PSO) algorithm, where the choice of the parameters is inspired by 4, in order to avoid diverging trajectories of the particles,and help the exploration of the feasible set.Moreover, we extend the ideas in 4 and propose a specific set of initial particles position for the bound constrained problem.

关键词： Bound Constrained Optimization Discrete Dynamic Linear Systems Free and Forced Responses Particles Initial Position

作者: Emilio Fortunato Campana Matteo Diez Giovanni Fasano Daniele Peri

作者单位: National Research Council-Maritime Research Centre (CNR-INSEAN),Via di Vallerano, 139, 00128 Rome, I University CaFoscari of Venice, Department of Management

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 112-119

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）