The Performance of Genetic Algorithms on Solving the Pickup and Delivery Vehicle Routing Problem
This study examines the performance of genetic algorithms (GAs) on solving a pickup and delivery vehicle routing problem, typically faced by home delivery service providers. A number of combinations of GA's three main algorithmic operators, namely, selection, crossover, and mutation is implemented, and the data envelopment analysis (DEA) is adopted to evaluate and rank these various combinations of GA operators. The numerical results demonstrate that DEA is appropriate in determining the efficient combinations of GA operators. Among the combinations under consideration, the combination using tournament selection and simple crossover is generally more efficient. The findings also contribute to algorithm development and evaluation of vehicle routing problems from the operations research perspective.
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- Summary URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/21855560
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Authors:
- LU, Chung-Cheng
- YANG, Cheng-Yao
- Publication Date: 2012
Language
- English
- Japanese
Media Info
- Media Type: Digital/other
- Features: References; Tables;
- Pagination: pp 64-79
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Serial:
- Asian Transport Studies
- Volume: 2
- Issue Number: 1
- Publisher: Eastern Asia Society for Transportation Studies
- EISSN: 2185-5560
- Serial URL: https://www.jstage.jst.go.jp/browse/eastsats
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Delivery vehicles; Genetic algorithms; Operations; Pickup and delivery service; Routing; Time windows
- Subject Areas: Freight Transportation; Planning and Forecasting; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01504735
- Record Type: Publication
- Source Agency: Japan Science and Technology Agency (JST)
- Files: TRIS, JSTAGE
- Created Date: Jan 27 2014 9:40AM