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A knowledge-based approach for multi-factory production systems
Affiliation:1. Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China;2. Department of Plastic and Cosmetic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China;1. Department of Management, Faculty of Social Sciences, Bar-Ilan University, Ramat Gan, 5290002 Israel;2. School of Management and Economics, The Academic College of Tel Aviv-Yaffo, Tel Aviv-Yaffo, 61083 Israel
Abstract:This paper investigates scheduling of jobs with deadlines across a serial multi-factory supply chain which involves minimizing sum of total tardiness and total transportation costs. Jobs can be transported among factories and can be delivered to the customer in batches which have limited capacity. The aim of this optimization problem is threefold: (1) determining the number of batches, (2) assigning jobs to batches, and (3) scheduling the batches production and delivery in each factory. The proposed problem formulated as a mixed-integer linear program. Then the model's performance is analyzed and evaluated through two examples. Moreover, a knowledge-based imperialistic competitive algorithm (KBICA) is also presented to find an approximate optimum solution for the problem. Computational experiments of the proposed problem investigate the efficiency of the method through different sizes of the test problems.
Keywords:Multi-factory production systems  Batch delivery  Mixed-integer programming  Knowledge-based approach  Imperialist competitive algorithm
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