Earticle

초록

영어

To solve the slow convergence speed, low precision in later period and tedious parameter setting of differential evolution when applied to complex optimization functions, an improved differential evolution algorithm (dn-DADE) based on dynamic adaptive strategy is proposed. Firstly, the elite solutions of current population are utilized in the new mutation strategy (DE/current-to-dnbest/1) to guide the search direction, and then these optional elite solutions tend to the global optimal solution in the late stage of evolution to balance the diversity of population and convergence speed. Secondly, the adaptive update strategies of scaling factor and crossover factor are designed for control parameter values self-adapting at different search stages, thus improve the stability and robustness of the algorithm. A set of 14 benchmark functions is adopted to test the performance of the proposed algorithm. The results show that dn-DADE algorithm has the advantages of remarkable optimizing ability, higher search precision, faster convergence speed and outperforms several state-of-the-art improved differential evolution algorithms in terms of the main performance indexes.

목차

Abstract
 1. Introduction
 2. Classical Differential Evolution Algorithm
 3. Improved Differential Evolution Algorithm based on Dynamic Adaptive Strategies
  3.1. Mutation Strategy
  3.2. Dynamic Adaptive Strategies of Parameters
  3.3 Realization of the dn-DADE Algorithm
 4. Experiments and Results
  4.1. Test Functions
  4.2. Experimental Setup
  4.3. Comparison of dn-DADE with Other Advanced Optimization Algorithms
  4.4. The Benefit of dn-DADE Components
  4.5. Parameter Analysis
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Congjiao Wang [ Department of Electrical Engineering and Automation, Shanghai Maritime University, Shanghai 201306, China ]
• Xihuai Wang [ Department of Electrical Engineering and Automation, Shanghai Maritime University, Shanghai 201306, China ]
• Jianmei Xiao [ Department of Electrical Engineering and Automation, Shanghai Maritime University, Shanghai 201306, China ]
• Yi Ding [ Department of Electrical Engineering and Automation, Shanghai Maritime University, Shanghai 201306, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605