International Journal of Computational Intelligence Systems

<Previous Article In Issue
Next Article In Issue>
Volume 12, Issue 2, 2019, Pages 530 - 543

An Efficient Modified Particle Swarm Optimization Algorithm for Solving Mixed-Integer Nonlinear Programming Problems

Authors
Ying Sun1, Yuelin Gao2, *
1School of Computer Science and Information Engineering, Hefei University of Technology, No.193 Tunxi Road, Hefei, 230009, PR China
2Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, No.204 Wenchang North Street, Yinchuan, 750021, PR China
*Corresponding author. Email: gaoyuelin@263.net
Corresponding Author
Yuelin Gao
Received 5 August 2018, Accepted 28 March 2019, Available Online 12 April 2019.
DOI
10.2991/ijcis.d.190402.001How to use a DOI?
Keywords
Particle swarm optimization; Mixed-integer nonlinear programming; Constrained optimization; Simulated annealing
Abstract

This paper presents an efficient modified particle swarm optimization (EMPSO) algorithm for solving mixed-integer nonlinear programming problems. In the proposed algorithm, a new evolutionary strategies for the discrete variables is introduced, which can solve the problem that the evolutionary strategy of the classical particle swarm optimization algorithm is invalid for the discrete variables. An update strategy under the constraints is proposed to update the optimal position, which effectively utilizes the available information on infeasible solutions to guide particle search. In order to evaluate and analyze the performance of EMPSO, two hybrid particle swarm optimization algorithms with different strategies are also given. The simulation results indicate that, in terms of robustness and convergence speed, EMPSO is better than the other algorithms in solving 14 test problems. A new performance index (NPI) is introduced to fairly compare the other two algorithms, and in most cases the values of the NPI obtained by EMPSO were superior to the other algorithms.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 2
Pages
530 - 543
Publication Date
2019/04/12
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.190402.001How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Ying Sun
AU  - Yuelin Gao
PY  - 2019
DA  - 2019/04/12
TI  - An Efficient Modified Particle Swarm Optimization Algorithm for Solving Mixed-Integer Nonlinear Programming Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 530
EP  - 543
VL  - 12
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.190402.001
DO  - 10.2991/ijcis.d.190402.001
ID  - Sun2019
ER  -