This article discusses a multi-item planning and scheduling problem in a job-shop system with consideration of energy consumption. Planning is considered by a set of periods, each one is characterized by a demand, energy, and length. Scheduling is determined by the sequences of jobs on available resources. A Mixed-Integer Linear Programming (MILP) problem is formulated to integrate planning and scheduling, it is considered as an NP-difficult problem. A Genetic Algorithm (GA) is then developed to solve the MILP, and then a hybridized approach of simulated annealing with genetic algorithm (HGASA) is presented to optimize the results. Finally, numerical results are presented and analyzed to evaluate the effectiveness of the proposed algorithms.
A Comparative Analysis of Metaheuristic Approaches (Genetic Algorithm/Hybridization of Genetic Algorithms and Simulated Annealing) for Planning and Scheduling Problem with Energy Aspect
Sae Int. J. Mater. Manf
Sae International Journal of Materials and Manufacturing
Sae International Journal of Materials and Manufacturing ; 14 , 4 ; 363-373
2021-05-20
11 pages
Aufsatz (Konferenz)
Englisch
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