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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qing Li Guangjun Liu Wei Zhang Cailu Zhao Yixin Yin Zhiliang Wang |
| Copyright Year | 2006 |
| Description | Author affiliation: Sch. of Inf. Eng., Beijing Univ. of Sci. & Technol. (Qing Li) |
| Abstract | A specific genetic algorithm is proposed in this paper for optimum path planning. Operations such as encoding, crossover and mutation are tailored to fit optimum path planning. Simulation results show that the specific genetic algorithm has advantages such as rapid calculation speed and high probability of optimal solution. It is a new approach for solving shortest path problems in practical GIS and ITS |
| Starting Page | 140 |
| Ending Page | 143 |
| File Size | 4275743 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780395867 |
| DOI | 10.1109/ITST.2006.288799 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-06-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Geographic Information Systems vehicle guidance Genetic mutations optimum path planning Probability Path planning Encoding Intelligent transportation systems Biological cells Genetic algorithms Shortest path problem genetic algorithm shortest path problem Artificial intelligence |
| Content Type | Text |
| Resource Type | Article |
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