An Evolutionary Space Search Algorithm (ESSA) for global numerical optimization

Tzyy Chyang Lu, Jyh Ching Juang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This work presents an optimization method combined with evolutionary space search algorithm (ESSA) for solving numerical optimization problems. The main strategy of the ESSA is to divide the feasible solution space into many subspaces and search for the solution by finding the optimal subspace. To facilitate the global exploration property, the subspace is characterized in terms of quantum bit representation and selected based on selection probabilities. As differences in fitness are evaluated with each generation, the quantum bits also evolve gradually. This process increases the probability of selecting subspaces that generate better fitness and enables the algorithm to exploit good subspaces, which then promotes local exploitation capability. An overlapping strategy is developed to prevent the subspace search from being trapped at a local optimum. Applying the ESSA to ten benchmark functions of diverse complexities shows that the quantum evolution substantially enhances the search for an optimal solution by finding the subspace in which the optimal solution resides. Performance comparisons with other evolutionary algorithms (EAs) under the same termination condition are also presented to confirm the superiority and effectiveness of the ESSA.

Original languageEnglish
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Pages5768-5773
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 1
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: 2009 Dec 152009 Dec 18

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
CountryChina
CityShanghai
Period09-12-1509-12-18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'An Evolutionary Space Search Algorithm (ESSA) for global numerical optimization'. Together they form a unique fingerprint.

Cite this