thiruvady-lagrangianaco-2014.pdf (363.39 kB)
A Lagrangian-ACO matheuristic for car sequencing
journal contribution
posted on 2014-11-01, 00:00 authored by Dhananjay ThiruvadyDhananjay Thiruvady, A Ernst, M WallaceIn this study, we investigate a hybrid Lagrangian relaxation ant colony optimisation for optimisation version of the car sequencing problem. Several cars are required to be scheduled on an assembly line and each car requires a number of options such as sunroof and/or air conditioning. These cars are required to be sequenced such that sub-sequences of specific sizes may only include a limited number of any option. While this is usually a hard constraint, in this study we treat it as a soft constraint and further require the utilisation of options be modulated across the sequence leading to the optimisation problem. We investigate various Lagrangian heuristics, ant colony optimisation (ACO) and hybrids of these methods. The results show that the Lagrangian-ACO hybrid is the best performing method for up to 300 cars.
History
Journal
EURO journal on computational optimizationVolume
2Issue
4Pagination
279 - 296Publisher
SpringerLocation
Berlin, GermanyPublisher DOI
Link to full text
ISSN
2192-4406eISSN
2192-4414Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2014, EURO - The Association of European Operational Research SocietiesUsage metrics
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