Journal of Risk Analysis and Crisis Response

Volume 5, Issue 1, April 2015, Pages 47 - 53

Quantum-behaved Particle Swarm Optimization with Nelder-Mead Simplex Search Method

Authors
Weiquan Yao
Corresponding Author
Weiquan Yao
Received 6 December 2014, Accepted 8 February 2015, Available Online 1 April 2015.
DOI
https://doi.org/10.2991/jrarc.2015.5.1.4How to use a DOI?
Keywords
Swarm optimization,Nelder -Mead simplex method,hybrid algorithm, continuous optimization
Abstract
This paper proposes a novel hybrid algorithm based on quantum-behaved particle swarm optimization (QPSO) algorithm and Nelder-Mead (NM) simplex search method for continuous optimization problems, abbreviated as QPSO-NM. This hybrid algorithm is very easy to be implemented since it does not require continuity and differentiability of objective functions, and it also combines powerful global search ability of QPSO with precise local search of NM simplex method. In a suite of the first 10 test functions taken from CEC2005, QPSO-NM algorithm is compared with other four popular competitors and six special algorithms that are dedicated to solve CEC2005 test function suite. It is showed by the computational results that QPSO-NM outperforms other algorithms in terms of both convergence rate and solution accuracy. The proposed algorithm is extremely effective and efficient at locating optimal solutions for continues optimization.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
Journal of Risk Analysis and Crisis Response
Volume-Issue
5 - 1
Pages
47 - 53
Publication Date
2015/04
ISSN (Online)
2210-8505
ISSN (Print)
2210-8491
DOI
https://doi.org/10.2991/jrarc.2015.5.1.4How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Weiquan Yao
PY  - 2015
DA  - 2015/04
TI  - Quantum-behaved Particle Swarm Optimization with Nelder-Mead Simplex Search Method
JO  - Journal of Risk Analysis and Crisis Response
SP  - 47
EP  - 53
VL  - 5
IS  - 1
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2015.5.1.4
DO  - https://doi.org/10.2991/jrarc.2015.5.1.4
ID  - Yao2015
ER  -