Earticle

초록

영어

As an optimization technique, particle swarm optimization (PSO) has obtained much
attention during the past decade. It is gaining popularity, especially because of the speed of
convergence and the fact that it is easy to realize. To enhance the performance of PSO, an
improved hybrid particle swarm optimization (IPSO) is proposed to solve complex
optimization problems more efficiently, accurately and reliably. It provides a new way of
producing new individuals through organically merges the harmony search (HS) method into
particle swarm optimization (PSO). During the course of evolvement, harmony search is used
to generate new solutions and this makes IPSO algorithm have more powerful exploitation
capabilities. Simulation results and comparisons with the standard PSO based on several
well-studied benchmarks demonstrate that the IPSO can effectively enhance the searching
efficiency and greatly improve the search quality.

목차

Abstract
 1. Introduction
 2. Related works
  2.1. Standard PSO
  2.2. Harmony search
 3. The realization of IPSO based of HS
 4. Simulation results and comparisons
  4.1. Experimental parameters setting
  4.2. Test functions
  4.3. Experimental results
 5. Conclusions
 Refrenece:

저자

• LI Hong-qi [ Department of Computer Science and Technology, China University of Petroleum ]
• LI Li [ Department of Computer Science and Technology, China University of Petroleum ]
• Tai-hoon Kim [ Hannam University ]
• XIE Shao-long [ Resource Information School, China University of Petroleum ]

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