Parallel machine scheduling with job synchronization to enable efficient material flows in hub terminals

Peng Guo, Felix Weidinger and Nils Boysen

Omega, 2019, vol. 89, issue C, 110-121

Abstract: Hub terminals are important entities in today’s distribution networks. They exist for all means of transportation, e.g., cross docks for trucks, hub airports for aircraft, transshipment yards for freight trains, and container ports for vessels. This paper abstracts from the peculiarities of each application and presents a generic problem setting, which synchronizes inbound and outbound flows in general hub terminals. We derive a parallel machine scheduling problem with job synchronization. Jobs processed on machines represent vehicles loaded and/or unloaded at different service points. Whenever two vehicles aim to transfer loads among each other, they should simultaneously be processed, so that loads can directly be exchanged without intermediate storage and double-handling. To reach this general aim we predefine target transfer durations for job pairs and aim to maximize the weighted realized transfer durations. For this elementary problem, computational complexity is investigated and two mixed-integer programming models are introduced. Furthermore, an efficient and easily adaptable heuristic based on fix and optimize is presented. Finally, we show how to customize our generic model to specific hub terminals.

Keywords: Scheduling; Logistics; Hub terminals; Job synchronization (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.omega.2018.10.003

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