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논문검색

Multiple Constrained Dynamic Path Optimization based on Improved Ant Colony Algorithm

초록

영어

Vehicle navigation system can effectively alleviate traffic congestion, reduce pollution, and reduce travel cost and other problems. As is known to all, the traditional ones are all just static path planning with problems of not only weak effectiveness but also lack of standard optimal path options. They usually provide only one path which represents the shortest time or shortest distance, and ignore the actual demands of the dirivers. Based on traffic data of the past, the upcoming traffic flows can be estimated. With the help of the improved ant colony algorithm, the dynamic optimal path planning results will meet the need of the travelers according with multiple actual constraints.

목차

Abstract
 1. Introduction
 2. Current Research Status of the Path Planning Problems
 3. The Basic and Improved Ant Colony Algorithm
  3.1 Basic Ant Colony Algorithm
  3.2 Improved Ant Colony Algorithm
  3.3 The Optimal Routing Selection based on Ant Colony Algorithm
 4. Case Study 
  4.1 Targets
  4.2 Simulation and Analysis
 5. Conclusions
 Acknowledgements
 References

저자정보

  • Seng Dewen School of Software Engineering, Hangzhou Dianzi University, 310018, Hangzhou, China
  • Tang Meixia School of Software Engineering, Hangzhou Dianzi University, 310018, Hangzhou, China
  • Wu Hao School of Software Engineering, Hangzhou Dianzi University, 310018, Hangzhou, China
  • Fang Xujian School of Software Engineering, Hangzhou Dianzi University, 310018, Hangzhou, China
  • Xu Haitao School of Software Engineering, Hangzhou Dianzi University, 310018, Hangzhou, China

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