A memetic algorithm for minimizing the makespan in the Job Shop Scheduling problem

Authors

  • Henry Lamos-Díaz Ph. D. Universidad Industrial de Santander (Bucaramanga-Santander, Colombia).
  • Karin Aguilar-Imitola M. Sc. Universidad Industrial de Santander (Bucaramanga-Santander, Colombia).
  • Yuleiny Tatiana Pérez-Díaz Esp. Universidad Industrial de Santander (Bucaramanga-Santander, Colombia).
  • Silvia Galván-Núñez M. Sc. Universidad Industrial de Santander (Bucaramanga-Santander, Colombia).

DOI:

https://doi.org/10.19053/01211129.v26.n44.2017.5776

Keywords:

Job Shop Schedule, local search, memetic algorithm, metaheuristics

Abstract

The Job Shop Scheduling Problem (JSP) is a combinatorial optimization problem cataloged as type NP-Hard. To solve this problem, several heuristics and metaheuristics have been used. In order to minimize the makespan, we propose a Memetic Algorithm (MA), which combines the exploration of the search space by a Genetic Algorithm (GA), and the exploitation of the solutions using a local search based on the neighborhood structure of Nowicki and Smutnicki. The genetic strategy uses an operation-based representation that allows generating feasible schedules, and a selection probability of the best individuals that are crossed using the JOX operator. The results of the implementation show that the algorithm is competitive with other approaches proposed in the literature.

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Published

2017-01-25

How to Cite

Lamos-Díaz, H., Aguilar-Imitola, K., Pérez-Díaz, Y. T., & Galván-Núñez, S. (2017). A memetic algorithm for minimizing the makespan in the Job Shop Scheduling problem. Revista Facultad De Ingeniería, 26(44), 113–123. https://doi.org/10.19053/01211129.v26.n44.2017.5776

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