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- Publisher
- Inderscience Publishers
- Copyright
- Copyright © Inderscience Enterprises Ltd. All rights reserved
- ISSN
- 1748-1252
- eISSN
- 1748-1260
- DOI
- 10.1504/IJENM.2012.047620
- Publisher site
- See Article on Publisher Site
Abstract
Evolutionary computation is an effective tool for solving optimisation problems. However, its significant computational demand has limited its real-time and online applications, e.g., mobile vehicles in supply chains. An enhanced SA approach incorporating with initial path selection heuristics and multiple mathematical operators is proposed in this paper for vehicle path planning in dynamic supply chain environments. It requires less computation times while giving better trade-offs among simplicity, far-field accuracy, and computational cost. The enhanced SA is analysed in several environments. The evaluation results demonstrate the ESA approach has the best performance for vehicle path planning in dynamic supply chains.
Journal
International Journal of Enterprise Network Management – Inderscience Publishers
Published: Jan 1, 2012