Multiscale Quantum Harmonic Oscillator Algorithm for Multimodal Optimization

Abstract EN

This paper presents a variant of multiscale quantum harmonic oscillator algorithm for multimodal optimization named MQHOA-MMO.

MQHOA-MMO has only two main iterative processes: quantum harmonic oscillator process and multiscale process.

In the two iterations, MQHOA-MMO only does one thing: sampling according to the wave function at different scales.

A set of benchmark test functions including some challenging functions are used to test the performance of MQHOA-MMO.

Experimental results demonstrate good performance of MQHOA-MMO in solving multimodal function optimization problems.

For the 12 test functions, all of the global peaks can be found without being trapped in a local optimum, and MQHOA-MMO converges within 10 iterations.