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Using a permutation representation genetic algorithm to implement a complex pick up/drop off mathematical model

Choudry, Sundas; Serpell, Martin C.; Burnham, Paul

Authors

Sundas Choudry

Martin Serpell Martin2.Serpell@uwe.ac.uk
Senior Lecturer in Computer Systems and Networks

Paul Burnham



Abstract

The Variable Message Sign Problem (VMSP) aims to optimise the delivery, collection and maintenance of Variable Message Signs. Firstly, the problem was formulated as a rigorous mathematical model. It was then reformulated using a permutation representation removing the need for some hard constraints and the formation of illegal sub-tours within the solution. The reformulated model was shown to be solvable using different artificial intelligence search techniques. The problem of parameter selection was then solved using self-adaption, which produced superior solutions with >99.9% confidence by avoiding numerous local optima on the fitness landscape.

Journal Article Type Article
Publication Date Jul 1, 2019
Journal Applied Soft Computing
Print ISSN 1568-4946
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 80
Pages 810-819
APA6 Citation Serpell, M. C., Choudry, S., & Burnham, P. (2019). Using a permutation representation genetic algorithm to implement a complex pick up/drop off mathematical model. Applied Soft Computing, 80, 810-819. https://doi.org/10.1016/j.asoc.2019.03.036
DOI https://doi.org/10.1016/j.asoc.2019.03.036
Keywords Variable message sign problem, genetic algorithm, self-adaption, mathematical model, vehicle routing, pick-up/drop-off
Publisher URL https://doi.org/10.1016/j.asoc.2019.03.036
Additional Information This is the author's accepted manuscript. The final published version is available here: https://doi.org/10.1016/j.asoc.2019.03.036.

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Copyright Statement
This is the author's accepted manuscript. The final published version is available here: https://doi.org/10.1016/j.asoc.2019.03.036.







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