In this paper we propose PSO–EDA, a hybrid particle swarm optimization (PSO) with estimation of distribution algorithm (EDA) to solve permutation flowshop scheduling problem (PFSP). PFSP is an NP-complete problem, for which PSO was recently applied. The social cognition in the metaphor of canonical PSO is incomplete, since information conveyed in the non-gbest particles is lost. Also, the intel...

The single-stage scheduling problem to minimize the makespan of identical jobs with general release times on uniform parallel machines is known to be solvable in polynomial time using the latest start time (LST) rule to determine the optimal schedule. In this paper, we first show that the two-stage problem is NP-hard using a known result that the three-stage problem with equal job release times...

This paper addresses a realistic variant of the Hybrid Flow Shop (HFS) problem, based on a real microelectronics manufacturing environment. Firstly, the formulation of a Mixed Integer Linear Programming (MILP) model for optimally solving the problem is provided. Then, two metaheuristic procedures are presented: the former is a genetic algorithm based on an encoding/decoding method well-known in...