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Planning and optimising organisational travel plans using an evolutionary algorithm.

Urquhart, Neil B

Authors



Contributors

Cecilia Chio
Editor

Anthony Brabazon
Editor

Gianni A Caro
Editor

Rolf Drechsler
Editor

Muddassar Farooq
Editor

J�rn Grahl
Editor

Gary Greenfield
Editor

Christian Prins
Editor

Juan Romero
Editor

Giovanni Squillero
Editor

Abstract

Commuting to the workplace is a highly individualistic experience, especially where the private car is the chosen mode of transport. The costs of using cars with low occupancy rates are significant in environmental terms as well as requiring the provision of parking space at the workplace. This paper examines the use of an Evolutionary Algorithm based problem solver to construct travel plans for three sites with 248,404 and 520 employees respectively at each site. Results presented suggest that a significant saving in overall distance travelled and parking spaces required is possible. The algorithm employed takes into account both hard constraints and soft constraints (such as work patterns and journey flexibility).

Citation

Urquhart, N. B. (2011). Planning and optimising organisational travel plans using an evolutionary algorithm. In C. Chio, A. Brabazon, G. A. Caro, R. Drechsler, M. Farooq, J. Grahl, …G. Squillero (Eds.), Applications of Evolutionary Computation (464-470). https://doi.org/10.1007/978-3-642-20520-0_47

Conference Name European Conference on the Applications of Evolutionary Computation
Start Date Apr 27, 2011
End Date Apr 30, 2011
Publication Date 2011
Deposit Date Jun 27, 2011
Publicly Available Date Mar 28, 2024
Peer Reviewed Peer Reviewed
Volume 6625
Pages 464-470
Series Title Lecture Notes in Computer Science
Series Number 6625
Series ISSN 0302-9743
Book Title Applications of Evolutionary Computation
ISBN 9783642205194
DOI https://doi.org/10.1007/978-3-642-20520-0_47
Keywords Evolutionary algorithm; transport; commuting; journey planning; private car;
Public URL http://researchrepository.napier.ac.uk/id/eprint/4549
Publisher URL http://dx.doi.org/10.1007/978-3-642-20520-0_47

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