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A Meta-Heuristic Approach for a Special Class of Job Shop Scheduling Problem
Behroozi, Mehdi | 2009
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 39179 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Koorosh, Eshghi
- Abstract:
- The job shop scheduling problem is an important and applicable optimization problem and has been attracted by many researchers in recent decades. A huge amount of applications of job shop scheduling problem in industries and services has been found yet. During the last decade, the sequence dependent setup time constraint has been considered in many researches, but with respect to the knowledge of authors, very few of these researches have considered the inseparable setup. Furthermore, few of them have considered the release date assumption. In this thesis, the classical job shop scheduling problem and the inseparable sequence dependent setup time and release date constrained problem have been considered in a deterministic environment with makespan minimization as an objective function. A mixed integer linear programming model has been developed for this problem. To represent the solutions of the problem a preference list-based representation method has been used and a heuristic algorithm for decoding represented solutions by this representation has been developed. To solve the problem a new exact algorithm for transforming a solution to an active schedule together with a new metaheuristic algorithm based on greedy randomized adaptive search procedure and a new hybrid particle swarm optimization that is called HPSO has been developed for solving the problem. Furthermore, a new method has been developed to conform the discrete solutions of scheduling problem to continuous solutions of particle swarm optimization algorithm. The HPSO algorithm has been applied on some benchmark problems and the obtained results indicates the accuracy and efficiency of solutions comparison with other algorithms for solving these problems
- Keywords:
- Sequence Dependent Setup ; Scheduling ; Job Shop ; Particles Swarm Optimization (PSO) ; Inseparable Setup ; Greedy Randomized Adaptive Search Procedure (GRASP) ; Release Data
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