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A Comprehensive Survey of Test Functions for Evaluating the Performance of Particle Swarm Optimization Algorithm

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJHIT) 바로가기
  • 간행물
    International Journal of Hybrid Information Technology 바로가기
  • 통권
    Vol.8 No.5 (2015.05)바로가기
  • 페이지
    pp.97-104
  • 저자
    Er. Avneet Kaur, Er. Mandeep Kaur
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A246041

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원문정보

초록

영어
Test functions play an important role in validating and comparing the performance of optimization algorithms. The test functions should have some diverse properties, which can be useful in testing of any new algorithm. The efficiency, reliability and validation of optimization algorithms can be done by using a set of standard benchmarks or test functions. For any new optimization, it is necessary to validate its performance and compare it with other existing algorithms using a good set of test functions. Optimization problems are widely used in various fields of science and technology. Sometimes such problems can be very complex. Particle Swarm Optimization is a stochastic algorithm used for solving such optimization problems. This paper transplants some of the test functions which can be used to test the performance of Particle Swarm Optimization (PSO) algorithm, in order to improve its performance and have better results. Different test functions can be used for different types of problems. These test functions have a specific range and values, which can be applied in different situations. These functions, when applied to the PSO algorithm, can give the better comparison of results. The test functions that have been the most commonly adopted to assess performance of PSO-based algorithms and details of each of them are provided, such as the search range, the position of their known optima, and other relevant properties.

목차

Abstract
 1. Introduction
 2. Particle Swarm Optimization Technique
  2.1. Particle Swarm Optimization
  2.2. PSO Algorithm
  2.3. Principles of PSO Algorithm
  2.4. Analysis of PSO Algorithm
 3. Test Functions
 4. Generating a Test Function
 5. Evaluating Test Functions for Assessing the Performance of Particle Swarm Optimization
 6. Implementation and Results
 7. Related Work
 8. Conclusion and Future Scope
 References

키워드

test functions bird flock inertia weight optimum point optimization optimization algorithms optimization problems Particle swarm optimization performance search space optimum

저자

  • Er. Avneet Kaur [ Student ,Computer Science Department, Guru Nanak Dev University, Regional Campus, Jalandhar. Lecturer, Computer Science Department, Guru Nanak Dev University, Regional Campus, Jalandhar, India ]
  • Er. Mandeep Kaur [ Student ,Computer Science Department, Guru Nanak Dev University, Regional Campus, Jalandhar. Lecturer, Computer Science Department, Guru Nanak Dev University, Regional Campus, Jalandhar, India ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Hybrid Information Technology
  • 간기
    격월간
  • pISSN
    1738-9968
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

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