Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach

Fateme Heidari, Seyed Hessameddin Zegordi () and Reza Tavakkoli-Moghaddam
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Fateme Heidari: Industrial Engineering of Tarbiat Modares University
Seyed Hessameddin Zegordi: Tarbiat Modares University
Reza Tavakkoli-Moghaddam: University of Tehran

Journal of Intelligent Manufacturing, 2018, vol. 29, issue 5, No 12, 1155-1170

Abstract: Abstract Uncertainty and non-deterministic nature of the real world makes planning and scheduling in cross-docks a very complicated task for decision makers. These constant changes that happen all the time, often, lead to an increase in costs and/or a decrease in efficiency. Most of the uncertainty in cross-docks is caused by un-known truck arrival times. In this study we address the problem of scheduling incoming and outgoing trucks at a cross-dock facility, when vehicle arrival times are unknown, through a cost-stable scheduling strategy. Two meta-heuristics, MODE and NSGA-II, are used for solving the designed sample problems and are compared with a random search based genetic algorithm existing in the literature. Finally, performance of each algorithm is measured and analyzed using four metrics: quality, spacing, diversification and mean ideal distance. The results indicate that the proposed model MODE algorithm performs better in comparison with the other two methods.

Keywords: Cross-dock facilities; Supply chain management; Unknown arrival time; Scheduling; Bi-objective bi-level optimization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s10845-015-1160-3

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