Initial Particles Position for PSO, in Bound Constrained Optimization

Initial Particles Position for PSO, in Bound Constrained Optimization

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 derivativefree 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 obje...

Global optimization algorithms for bound constrained problems

Particle Swarm Optimization (PSO) based Tool Position Error Optimization

High-precision tool positioning is one of the fundamental requirements for the industry now-a-days. Earlier, tool positioning and its verification were done using sensors etc. In this paper, an algorithm has been proposed to increase the tool positioning accuracy by analyzing the information obtained using CCD camera. The images of lathe tool are used for carrying out the experiments. Firstly, ...

Hybrid PSO-tabu search for constrained non-linear optimization problems

In this paper we present a new method to solve a constrained non-linear problem. The method is based on hybridizing the Particle Swarm Optimization and tabu-search meta-heuristics (PSOTS). Tow tabu-lists are used within the PSO algorithm: the first one aims to diversify the best solutions obtained by particles when the second bans temporarily solutions non-respecting the constraints. The obtain...

Recent Advances in Bound Constrained Optimization

A new active set algorithm (ASA) for large-scale box constrained optimization is introduced. The algorithm consists of a nonmonotone gradient projection step, an unconstrained optimization step, and a set of rules for switching between the two steps. Numerical experiments and comparisons are presented using box constrained problems in the CUTEr and MINPACK test problem libraries. keywords: Nonm...