ABSTRACT This paper addresses the scheduling of supply chains with interrelated factories consisting of a single vendor and multiple customers. In this research, one transporter is available to deliver jobs from vendor to customers, and the jobs can be processed by batch. The problem studied in this paper focuses on a real-case scheduling problem of a multi-location hospital supplied with a central pharmacy. The objective of this work is to minimize the total cost, while satisfying the customer’s due dates constraints. A mathematical formulation of the problem is given as a Mixed Integer Programming model. Then, a Branch-and-Bound algorithm is proposed as an exact method for solving this problem, a greedy local search is developed as a heuristic approach, and a hybrid Genetic Algorithm is presented as a meta-heuristic. Computation experiments are conducted to highlight the performance of the proposed methods.

中文翻译：

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一种混合遗传算法方法来最小化单供应商多客户集成调度问题的总联合成本

摘要 本文讨论了由一个供应商和多个客户组成的相互关联的工厂的供应链调度。在这项研究中，可以使用一个运输车将作业从供应商交付给客户，并且可以批量处理作业。本文研究的问题集中在一个设有中央药房的多地点医院的实际调度问题上。这项工作的目标是最小化总成本，同时满足客户的到期日限制。该问题的数学公式作为混合整数规划模型给出。然后，提出了分支定界算法作为解决该问题的精确方法，开发了贪婪局部搜索作为启发式方法，并提出了混合遗传算法作为元启发式方法。