UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Unimodal optimization using a genetic-programming-based method with periodic boundary conditions

Póvoa, RCBL; Koshiyama, AS; Dias, DM; Souza, PL; Horta, BAC; (2020) Unimodal optimization using a genetic-programming-based method with periodic boundary conditions. Genetic Programming and Evolvable Machines , 21 pp. 503-523. 10.1007/s10710-019-09373-1. Green open access

[thumbnail of Koshiyama_AAMUnimodal_optimization_through_a_niching_method_and_molecular_modeling.pdf]
Preview
Text
Koshiyama_AAMUnimodal_optimization_through_a_niching_method_and_molecular_modeling.pdf - Accepted Version

Download (1MB) | Preview

Abstract

This article describes a new genetic-programming-based optimization method using a multi-gene approach along with a niching strategy and periodic domain constraints. The method is referred to as Niching MG-PMA, where MG refers to multi-gene and PMA to parameter mapping approach. Although it was designed to be a multimodal optimization method, recent tests have revealed its suitability for unimodal optimization. The definition of Niching MG-PMA is provided in a detailed fashion, along with an in-depth explanation of two novelties in our implementation: the feedback of initial parameters and the domain constraints using periodic boundary conditions. These ideas can be potentially useful for other optimization techniques. The method is tested on the basis of the CEC’2015 benchmark functions. Statistical analysis shows that Niching MG-PMA performs similarly to the winners of the competition even without any parametrization towards the benchmark, indicating that the method is robust and applicable to a wide range of problems.

Type: Article
Title: Unimodal optimization using a genetic-programming-based method with periodic boundary conditions
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s10710-019-09373-1
Publisher version: https://doi.org/10.1007/s10710-019-09373-1
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Optimization, Evolutionary computation, Genetic programming, Niching methods, Periodic boundary conditions, Parameter mapping approach
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10092519
Downloads since deposit
305Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item