New Particle Swarm Optimization Algorithm For Makespan Minimization In Permutation Flowshop Sequencing

摘要

Particle Swarm Optimization (PSO) is a new type of heuristic inspired by the flocking behavior of birds. This paper presents a Particle Swarm Optimization (PSO) to solve the permutation flowshop scheduling problem (PFSP) objectives, to minimize the makespan. To this end, we have proposed the use of discrete PSO algorithm for the position of the smallest value (SPV) to use a random key representation of Bean [Baena Bean, Genetic algorithms and random keys sequencing and optimization, Orsa calculated Journal 6 (2) (1994) 154-160]. In the proposed algorithm, the particle and the velocity re-defined and effective way to develop a series of new particles. In addition, we analyzed the characteristics of the elite jobs in the proposed algorithm. The results showed that the idea really follows the approach of PSO.