SciELO - Scientific Electronic Library Online

vol.26 issue44Computational simulation of concentration by osmotic evaporation of passion fruit juice (Passiflora edullis)Spin Coating technique for obtaining nanometric thin films in the system La0.7Sr0.3MnO3 author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google


Revista Facultad de Ingeniería

Print version ISSN 0121-1129


LAMOS-DIAZ, Henry; AGUILAR-IMITOLA, Karin; PEREZ-DIAZ, Yuleiny Tatiana  and  GALVAN-NUNEZ, Silvia. A memetic algorithm for minimizing the makespan in the Job Shop Scheduling problem. Rev. Fac. ing. [online]. 2017, vol.26, n.44, pp.113-123. ISSN 0121-1129.

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.

Keywords : Job Shop Schedule; local search; memetic algorithm; metaheuristics.

        · abstract in Spanish | Portuguese     · text in English     · English ( pdf )