Earticle

초록

영어

The traditional genetic algorithm randomly selects nodes in two chromosomes for crossover operation, which may result in individuals of disconnected or loop circuit and lead to issues as meaningless crossover operations. In order to increase the diversity of the population and prevent the occurrence of premature mutation algorithm which might cause local convergence, this essay presents a new urban traffic optimal path planning method. Initialized from the improvement of population genetic algorithm, it designs the fitness function and optimizes crossover and mutation operators so that the optimal or near-optimal solution can be quickly figured out. Moreover, the Matlab software simulation test exhibits the feasibility and effectiveness of the method.

목차

Abstract
 1. Introduction
 2. The Urban Traffic Optimal Path Design based on Genetic Agorithms
  2.1 Population Initialization
  2.2 Fitness Function Design
  2.3 Improved Crossover Operator
  2.4. Improved Mutation Operator
 3. Experimental Verification
 4. Conclusion
 References

키워드

저자

• Xuejun Liu [ School of Urban Design, Wuhan University, Wuhan, China ]
• Yihan Chen [ School of Urban Design, Wuhan University, Wuhan, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605