A Genetic Algorithm for the Parallel Machine Scheduling Problem with Consumable Resources

Fayçal Belkaid, Zaki Sari and Mehdi Souier
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Fayçal Belkaid: Manufacturing Engineering Laboratory of Tlemcen, University of Tlemcen, Tlemcen, Algeria
Zaki Sari: Manufacturing Engineering Laboratory of Tlemcen, University of Tlemcen, Tlemcen, Algeria
Mehdi Souier: Manufacturing Engineering Laboratory of Tlemcen, University of Tlemcen, Tlemcen, Algeria, & Tlemcen Preparatory School of Economics, Tlemcen, Algeria

International Journal of Applied Metaheuristic Computing (IJAMC), 2013, vol. 4, issue 2, 17-30

Abstract: In this paper, the authors’ interest is focused on the scheduling problem on identical parallel machines with consumable resources in order to minimize the makespan criterion. Each job consumes several components which arrive at different times. The arrival of each component is represented by a curve-shaped staircase. This problem is NP-hard, further, there are not universal methods making it possible to solve all the cases effectively, especially for medium or large instances. A genetic algorithm is proposed to solve this problem due to proven great performance in solving combinatorial optimization problems. To check its effectiveness this algorithm is compared with an exact resolution method which enumerates all possible solutions for small instances and with a heuristic for large instances. Various randomly generated instances, which can represent realistic situations, are tested. The computation results show that this algorithm outperforms heuristic procedure and is tailored for larger scale problems.

Date: 2013
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