Title: Effect of potential well model for quantum heuristic algorithm: a comparative study and application

Authors: Jin Jin; Peng Wang

Addresses: Chengdu Institution of Computer Application, University of Chinese Academy of Sciences, Chengdu 610041, China ' School of Computer Science and Technology, Southwest Minzu University, Chengdu, 610225, China

Abstract: The multiscale quantum harmonic-oscillator algorithm (MQHOA) is an intelligent optimisation algorithm based on quantum harmonic wave functions. Although it is effective for many optimisation problems, an analysis for its performance is still lacking. This paper discusses the harmonic-oscillator potential well, delta-function potential well, and infinite-square potential well in terms of their application in evolutionary algorithms. Of the three, the harmonic-oscillator potential well is considered to give the most precise approximation for complex objective functions. To verify its global optimisation performance, experiments are conducted using a suite of benchmark functions to compare the performance of different potential wells and heuristic algorithms. The experimental results indicate that MQHOA with the harmonic-oscillator potential well is a better practical choice than the other two potential well models, and show that MQHOA is a potential quantum heuristic algorithm.

Keywords: multiscale quantum harmonic-oscillator algorithm; MQHOA; quantum heuristic algorithm; global optimisation; potential well; wave function.

DOI: 10.1504/IJBIC.2022.123108

International Journal of Bio-Inspired Computation, 2022 Vol.19 No.3, pp.178 - 188

Received: 20 Jan 2020
Accepted: 27 Sep 2020
Published online: 30 May 2022 *

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