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A simulation optimization approach for flow-shop scheduling problem: a canned fruit industry

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Abstract

Flow-shop scheduling is one of the major problems in many manufacturing systems. Canned fruit is one of the industries in which the flow-shop scheduling has already been used. In this paper, an aggregated artificial neural network and simulation modeling approach are proposed to find optimal solution for such cases. Therefore, artificial neural network and simulation (ANNS) approach is introduced and used as a new approach to solve a certain flow-shop scheduling problem with the objective of minimizing total cost. In this research, flow-shop scheduling problem with parallel identical machines is investigated. The proposed approach is compared with the previous works, and the performance of the proposed approached is studied on a test problem. Experimental results show the superiority of the presented approach over conventional simulation approaches.

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Azadeh, A., Maleki-Shoja, B., Sheikhalishahi, M. et al. A simulation optimization approach for flow-shop scheduling problem: a canned fruit industry. Int J Adv Manuf Technol 77, 751–761 (2015). https://doi.org/10.1007/s00170-014-6488-x

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  • DOI: https://doi.org/10.1007/s00170-014-6488-x

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