Abstract
Currently, materials flow optimization and creating of optimal schedule are one of the main tasks of all companies for increase of competitiveness. A schedule problem in a manufacturing company is characterized as jobs sequence and allocation to machines during a time period. A variety of approaches have been developed to solve the problem of scheduling. However, many of these approaches are often impractical in dynamic real-world environments where there are complex constraints and a variety of unexpected disruptions. In this chapter cooperation of one meta-heuristic optimization algorithm with manufacturing model by the dynamical rescheduling is described. Particle Swarm Optimization algorithm solved scheduling problem of real manufacturing system. Model of the manufacturing system is represented as discrete event system created by SimEvents toolbox of MATLAB programing enviroment.
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Zelenka, J. (2012). Cooperation Particle Swarm Optimization with Discrete Events Systems by Dynamical Rescheduling. In: Fodor, J., Klempous, R., Suárez Araujo, C.P. (eds) Recent Advances in Intelligent Engineering Systems. Studies in Computational Intelligence, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23229-9_5
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DOI: https://doi.org/10.1007/978-3-642-23229-9_5
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