Large neighbourhood search based on mixed integer programming and ant colony optimisation for car sequencing
Version 2 2024-06-05, 04:39Version 2 2024-06-05, 04:39
Version 1 2019-07-17, 09:57Version 1 2019-07-17, 09:57
journal contribution
posted on 2024-06-05, 04:39 authored by Dhananjay ThiruvadyDhananjay Thiruvady, K Morgan, A Amir, AT Ernst© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. We investigate the problem of scheduling a sequence of cars to be placed on an assembly line. Stations, along the assembly line install options (e.g. air conditioning), but have limited capacities, and hence cars requiring the same options need to be distributed far enough apart. The desired separation is not always feasible, leading to an optimisation problem that minimises the violation of the ideal separation requirements. In order to solve the problem, we use a large neighbourhood search (LNS) based on mixed integer programming (MIP). The search is implemented as a sliding window, by selecting overlapping subsequences of manageable sizes, which can be solved efficiently. Our experiments show that, with LNS, substantial improvements in solution quality can be found.
History
Journal
International Journal of Production ResearchVolume
58Pagination
2696-2711Location
Abingdon, Eng.Publisher DOI
ISSN
0020-7543eISSN
1366-588XLanguage
EnglishNotes
In pressPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2019, Informa UK LimitedIssue
9Publisher
TAYLOR & FRANCIS LTDUsage metrics
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No categories selectedKeywords
Science & TechnologyTechnologyEngineering, IndustrialEngineering, ManufacturingOperations Research & Management ScienceEngineeringschedulingcar sequencinglarge neighbourhood searchmixed integer programmingant colony optimisationBEAM SEARCHACOMD Multidisciplinary4699 Other information and computing sciences
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