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Growing Science » Authors » Amir Noroozi

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1.

Coordinating order acceptance and integrated lot streaming-batch delivery scheduling considering third party logistics Pages 73-96 PDF Download PDF

Authors: Amir Noroozi, Mohammad Mahdavi Mazdeh, Mehdi Heydari, Morteza Rasti-Barzoki

doi 10.5267/j.uscm.2018.5.001

🔑 Keywords: Genetic algorithm, Order acceptance, Flexible flow shop, Lot streaming, Batch delivery, Third-party logistics

Abstract:
Inspired by the industries such as food and beverage, metal and steel, as well as petroleum and petrochemical ones, the current study addresses a joint order acceptance and scheduling, lot streaming in a flexible flow shop and batch delivery problem. For maximizing a profit objective function with trading off between the revenue of the accepted orders and the costs incurred, a novel mixed integer linear programming is proposed. This paper develops a hybrid metaheuristic algorithm based on the Genetic Algorithm. In the developed algorithm, (1) a heuristic, (2) a local search, and (3) a restart phase is proposed. To set the appropriate parameters of the algorithms, Taguchi experimental design was applied. The obtained results reveal the appropriate performance of the hybrid genetic algorithm.
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Journal: USCM | Year: 2019 | Volume: 7 | Issue: 1 | Views: 2493

 

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