Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time
This paper addresses the scheduling problem for customer orders on a set of unrelated parallel machines. Each order consists of multiple product types with various workloads that can be assigned to and processed by the machines. The objective is to minimise the total weighted completion time of all...
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Archīum Ateneo
2020
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ph-ateneo-arc.gsb-pubs-10012022-03-22T08:23:53Z Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time Li, Haidong Li, Zhen Zhao, Yaping Xu, Xiaoyun This paper addresses the scheduling problem for customer orders on a set of unrelated parallel machines. Each order consists of multiple product types with various workloads that can be assigned to and processed by the machines. The objective is to minimise the total weighted completion time of all customer orders. Several optimality properties are developed, and an easily computable lower bound is established. Besides, for two important special cases, the corresponding optimal schedules are further provided. Inspired by these results, three heuristic algorithms are proposed, and their worst case performances are proved to be bounded. The effectiveness of the lower bound and the proposed algorithms are demonstrated through numerical experiments. This study brings new perspectives to the management of differentiated customers in complicated production environment. 2020-01-01T08:00:00Z text https://archium.ateneo.edu/gsb-pubs/2 https://www.tandfonline.com/doi/full/10.1080/01605682.2020.1718010?casa_token=n2bqFEKBSW8AAAAA%3ADM3iliOLhXNtbwI3ndT_eLvyyu1pvuoaQR5uOTZdbiNVZFQcwvJ6XvM6tGytkoVzGv6ZyvIxXZN-XA Graduate School of Business Faculty Publications Archīum Ateneo Customer order scheduling unrelated parallel machines total weighted completion time Operations and Supply Chain Management |
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Customer order scheduling unrelated parallel machines total weighted completion time Operations and Supply Chain Management |
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Customer order scheduling unrelated parallel machines total weighted completion time Operations and Supply Chain Management Li, Haidong Li, Zhen Zhao, Yaping Xu, Xiaoyun Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
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This paper addresses the scheduling problem for customer orders on a set of unrelated parallel machines. Each order consists of multiple product types with various workloads that can be assigned to and processed by the machines. The objective is to minimise the total weighted completion time of all customer orders. Several optimality properties are developed, and an easily computable lower bound is established. Besides, for two important special cases, the corresponding optimal schedules are further provided. Inspired by these results, three heuristic algorithms are proposed, and their worst case performances are proved to be bounded. The effectiveness of the lower bound and the proposed algorithms are demonstrated through numerical experiments. This study brings new perspectives to the management of differentiated customers in complicated production environment. |
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Li, Haidong Li, Zhen Zhao, Yaping Xu, Xiaoyun |
author_facet |
Li, Haidong Li, Zhen Zhao, Yaping Xu, Xiaoyun |
author_sort |
Li, Haidong |
title |
Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
title_short |
Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
title_full |
Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
title_fullStr |
Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
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Scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
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scheduling customer orders on unrelated parallel machines to minimise total weighted completion time |
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Archīum Ateneo |
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2020 |
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https://archium.ateneo.edu/gsb-pubs/2 https://www.tandfonline.com/doi/full/10.1080/01605682.2020.1718010?casa_token=n2bqFEKBSW8AAAAA%3ADM3iliOLhXNtbwI3ndT_eLvyyu1pvuoaQR5uOTZdbiNVZFQcwvJ6XvM6tGytkoVzGv6ZyvIxXZN-XA |
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