Abstract
Job shop scheduling (JSS) problem is NP-hard in its simplest case and we generally need to add new constraints when we want to solve a JSS in any practical application area. Therefore, as its complexity increases we need algorithms that can solve the problem in a reasonable time period and can be modified easily for new constraints. In the literature, there are many metaheuristic methods to solve JSS problem. In this chapter, the proposed Ant algorithm can solve JSS problems in reasonable time and it is very easy to modify the artificial ants for new constraints. In addition, it is very easy to modify artificial ants for multiobjective cases.
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Kιlιç, S., Kahraman, C. (2006). Metaheuristic Techniques for Job Shop Scheduling Problem and a Fuzzy Ant Colony Optimization Algorithm. In: Kahraman, C. (eds) Fuzzy Applications in Industrial Engineering. Studies in Fuzziness and Soft Computing, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33517-X_17
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DOI: https://doi.org/10.1007/3-540-33517-X_17
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