Abstract
Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.
Highlights
Job shop production systems are considered as one of the most common forms of production systems in production systems
The proposed approach was based on a floating search procedure that has used some heuristic algorithms
First of all search is done upon assignment space achieving an acceptable solution and search would continue on sequencing space based on a heuristic algorithm
Summary
Job shop production systems are considered as one of the most common forms of production systems in production systems. An operation may be processed on more than one machine having the same function This leads to a more complex problem known as the flexible job-shop scheduling problem (FJSP). Kacem et al (2002) presented a hybrid approach based on fuzzy logic and multi-objective evolutionary algorithm to the problems of flexible job shop scheduling. They provided three objectives: minimization of make span, total workload and maximum workload of jobs in the models and prepare an appropriate solution seed structure for solving it.
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