Mixed binary integer programming formulations for the reentrant job shop scheduling problem
Computers and Operations Research
A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems
Computers and Operations Research
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In order to apply a continuous improvement of their production systems, all managers are always trying to improve their production systems by optimizing their scheduling method. This involves the search for efficient methods for obtaining the best results according to the costs and the delay criteria for example. This paper aims to solve a specific hybrid reentrant flow shop scheduling problem. This one contains some stages with some identical parallel machines. The orders sequenced are splited in batches. Each batch is processed one or more time on the system. For the resolution, various methods have been developed. An exact method which lists all the solutions and selects the best one and approximated methods such as the genetic algorithm GA, the genetic algorithm under fuzzy controller FLCGA, the particle swarm optimization PSO and the particle swarm optimization under fuzzy controller FLCPSO. The results discussed in the paper are very interesting.