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Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling

Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling

Jairo R. Montoya-Torres, Libardo S. Gómez-Vizcaíno, Elyn L. Solano-Charris, Carlos D. Paternina-Arboleda
Copyright: © 2010 |Volume: 1 |Issue: 4 |Pages: 12
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781613502983|DOI: 10.4018/joris.2010100103
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MLA

Montoya-Torres, Jairo R., et al. "Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling." IJORIS vol.1, no.4 2010: pp.47-58. http://doi.org/10.4018/joris.2010100103

APA

Montoya-Torres, J. R., Gómez-Vizcaíno, L. S., Solano-Charris, E. L., & Paternina-Arboleda, C. D. (2010). Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling. International Journal of Operations Research and Information Systems (IJORIS), 1(4), 47-58. http://doi.org/10.4018/joris.2010100103

Chicago

Montoya-Torres, Jairo R., et al. "Global Bacteria Optimization Meta-Heuristic Algorithm for Jobshop Scheduling," International Journal of Operations Research and Information Systems (IJORIS) 1, no.4: 47-58. http://doi.org/10.4018/joris.2010100103

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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.

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