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Hybrid Simulation and GA for a Flexible Flow Shop Problem with Variable Processors and Re-entrant Flow

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Applied Computer Sciences in Engineering (WEA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 915))

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Abstract

The problem of FFSP (Flexible Flow Shop Problem) has been sufficiently investigated due to its importance for production programming and control, although many of the solution methods have been based on GA (Genetic Algorithm) and simulation, these techniques have been used in deterministic environments and under specific conditions of the problem, that is, complying with restrictions given in the Graham notation. In this paper we describe an application of these techniques to solve a very particular case where manual work stations and equipment with different degrees of efficiency, technological restrictions, recirculation process are used. The nesting of the GA is used within a simulation process. It is showed that the method proposed in adjustment and efficiency is better compared with other heuristics, in addition to the benefits of using different techniques in series to solve problems of real manufacturing environments.

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Correspondence to German Mendez-Giraldo or Lindsay Alvarez-Pomar .

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Mendez-Giraldo, G., Alvarez-Pomar, L., Franco, C. (2018). Hybrid Simulation and GA for a Flexible Flow Shop Problem with Variable Processors and Re-entrant Flow. In: Figueroa-García, J., López-Santana, E., Rodriguez-Molano, J. (eds) Applied Computer Sciences in Engineering. WEA 2018. Communications in Computer and Information Science, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-00350-0_21

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  • DOI: https://doi.org/10.1007/978-3-030-00350-0_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00349-4

  • Online ISBN: 978-3-030-00350-0

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