An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation

Shouyong Jiang; Shengxiang Yang

doi:10.1109/CEC.2014.6900354

An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation

Shouyong Jiang^*, Shengxiang Yang

^*Corresponding author for this work

Computing Science

De Montfort University

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

9 Citations (Scopus)

Abstract

Quantum-behaved particle swarm optimization (QPSO) has shown to be an effective algorithm for solving global optimization problems that are of high complexity. This paper presents a new QPSO algorithm, denoted LI-QPSO, which employs a model-based linear interpolation method to strengthen the local search ability and improve the precision and convergence performance of the QPSO algorithm. In LI-QPSO, linear interpolation is used to approximate the objective function around a pre-chosen point with high quality in the search space. Then, local search is used to generate a promising trial point around this pre-chosen point, which is then used to update the worst personal best point in the swarm. Experimental results show that the proposed algorithm provides some significant improvements in performance on the tested problems.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	769-775
Number of pages	7
ISBN (Electronic)	9781479914883
DOIs	https://doi.org/10.1109/CEC.2014.6900354
Publication status	Published - 16 Sept 2014
Event	2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014

Publication series

Name	Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014

Conference

Conference	2014 IEEE Congress on Evolutionary Computation, CEC 2014
Country/Territory	China
City	Beijing
Period	6/07/14 → 11/07/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Access to Document

10.1109/CEC.2014.6900354

Cite this

Jiang, S., & Yang, S. (2014). An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 (pp. 769-775). Article 6900354 (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2014.6900354

An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation. / Jiang, Shouyong; Yang, Shengxiang.
Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 769-775 6900354 (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Jiang, S & Yang, S 2014, An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation. in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014., 6900354, Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 769-775, 2014 IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, 6/07/14. https://doi.org/10.1109/CEC.2014.6900354

Jiang S, Yang S. An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 769-775. 6900354. (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014). doi: 10.1109/CEC.2014.6900354

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An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation

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