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

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

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.

Citation

Choudry, S., Serpell, M. C., & 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

• Journal Article Type: Article
• Acceptance Date: Mar 21, 2019
• Online Publication Date: Mar 21, 2019
• Publication Date: Jul 1, 2019
• Deposit Date: Apr 29, 2019
• Publicly Available Date: Mar 22, 2020
• Journal: Applied Soft Computing
• Print ISSN: 1568-4946
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 80
• Pages: 810-819
• 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
• Public URL: https://uwe-repository.worktribe.com/output/850327
• 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.