Earticle

초록

영어

The extension of ant colony algorithm was proposed by Dorigo, the founder of ant colony algorithm, which is the latest ant colony algorithm for solving a continuous space optimization problem. Considering the blindness of man-made choice of initial solution and initial parameters of the algorithm, and according to the algorithm converging slowly and easily falling into local optimum, this paper has provided improvement strategy for this optimization. It has introduced quantum computing and genetic algorithm, chaos optimization to carry out combination and comparison, and it has carried out improvement on the weight internally solved by memory in the algorithm. The effectiveness of various combined algorithms was determined through the optimization of numerous multi-dimensional continuous functions.

목차

Abstract
 1. Introduction
 2. Extension of Ant Colony Algorithm
  2.1. The Process of Extension of Ant Colony Optimization
  2.2. Algorithm Analysis
 3. Improvement on ACOR Algorithm Integrated with Intelligent Algorithm
  3.1. Improvement on Extension of Ant Colony Algorithm Integrated with Genetic Algorithm
  3.2. Improvement on ACOR Integrated with Chaos Optimization
 4. Solving the Multi-dimensional Continuous Function by Improved ACOR
  4.1. Test Function
  4.2. Parameter Selection
  4.3. Simulation Result
 5. Conclusions
 References

키워드

저자

• Ma Li [ Engineering College, Northeast Agricultural University, China ]
• Li Qianting [ Engineering College, Northeast Agricultural University, China ]
• Ma Meiqiong [ Engineering College, Northeast Agricultural University, China ]
• Meng Jun [ College of Science, Northeast Agricultural University, Ha’erbin 150030, China ]
• Bai Jiyun [ College of Science, Northeast Agricultural University, Ha’erbin 150030, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605