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Simulating operations process to achieve a hybrid optimal operational performance in supply chain scheduling: a case study

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  • Salman Sigari

Abstract

One of the most challenging aspects of supply chain management is synchronising job-shop production and transportation in a network to guarantee on-time delivery to distributed customers. In multiple job-shop problems, there are j jobs that need to be processed by m machines with a certain objective function to be minimised and it has been classified as a combination problem. This study uses genetic algorithm (GA) with some modifications to deal with the problem of multiple job-shop scheduling. At the end, the most suitable machine arrangement would be presented from the program due to achieve sustainable supply chain management model.

Suggested Citation

  • Salman Sigari, 2016. "Simulating operations process to achieve a hybrid optimal operational performance in supply chain scheduling: a case study," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 23(2), pages 254-262.
    • Handle: RePEc:ids:ijisen:v:23:y:2016:i:2:p:254-262
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    Cited by:

    1. Tamás Bányai & Béla Illés & Miklós Gubán & Ákos Gubán & Fabian Schenk & Ágota Bányai, 2019. "Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach," Sustainability, MDPI, vol. 11(14), pages 1-26, July.

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