Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling

Jairo R. Montoya-Torres, Libardo S. Gómez-Vizcaíno, Elyn L. Solano-Charris and Carlos D. Paternina-Arboleda
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Jairo R. Montoya-Torres: Universidad de La Sabana, Colombia
Libardo S. Gómez-Vizcaíno: Fundación Centro de Investigación en Modelación Empresarial del Caribe, Colombia
Elyn L. Solano-Charris: Universidad de La Sabana, Colombia
Carlos D. Paternina-Arboleda: Universidad del Norte, Colombia

International Journal of Operations Research and Information Systems (IJORIS), 2010, vol. 1, issue 4, 47-58

Abstract: This paper examines the problem of jobshop scheduling with either makespan minimization or total tardiness minimization, which are both known to be NP-hard. The authors propose the use of a meta-heuristic procedure inspired from bacterial phototaxis. This procedure, called Global Bacteria Optimization (GBO), emulates the reaction of some organisms (bacteria) to light stimulation. Computational experiments are performed using well-known instances from literature. Results show that the algorithm equals and even outperforms previous state-of-the-art procedures in terms of quality of solution and requires very short computational time.

Date: 2010
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