Tadumadze, Giorgi ; Boysen, Nils ; Emde, Simon (2024)
Robust spotter scheduling in trailer yards.
In: OR Spectrum : Quantitative Approaches in Management, 2020, 42 (4)
doi: 10.26083/tuprints-00023872
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Robust spotter scheduling in trailer yards |
Language: | English |
Date: | 8 April 2024 |
Place of Publication: | Darmstadt |
Year of primary publication: | December 2020 |
Place of primary publication: | Berlin ; Heidelberg ; New York |
Publisher: | Springer |
Journal or Publication Title: | OR Spectrum : Quantitative Approaches in Management |
Volume of the journal: | 42 |
Issue Number: | 4 |
DOI: | 10.26083/tuprints-00023872 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | Spotters (also denoted as switchers) are specialized terminal tractors, which are dedicated to the rapid maneuvering of semitrailers between parking lot and dock doors in large trailer yards. This paper is dedicated to spotter scheduling, i.e., the assignment of predefined trailer movements to a given fleet of spotters. The limited number of dock doors for loading and unloading is often the scarce resource during trailer processing, so that idle time of the bottleneck, e.g., caused by unforeseen delay in the yard, is to be avoided. In this setting, we aim to insert time buffers between any pair of subsequent jobs assigned to the same spotter, so that small delays are not propagated and subsequent jobs can still be executed in a timely manner. We formalize two versions of the resulting robust spotter scheduling problem and provide efficient algorithms for finding optimal solutions in polynomial time. Furthermore, we simulate delays during the execution of spotter schedules and show that the right robustness objective can greatly improve yard performance. |
Uncontrolled Keywords: | Yard operations, Truck scheduling, Terminal tractor scheduling, Robustness |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-238721 |
Classification DDC: | 600 Technology, medicine, applied sciences > 650 Management |
Divisions: | 01 Department of Law and Economics > Betriebswirtschaftliche Fachgebiete > Fachgebiet Management Science / Operations Research |
Date Deposited: | 08 Apr 2024 12:41 |
Last Modified: | 10 Apr 2024 06:00 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23872 |
PPN: | 51699851X |
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