Artificial bee colony algorithm for large-scale problems and engineering design optimization


AKAY B., KARABOĞA D.

JOURNAL OF INTELLIGENT MANUFACTURING, vol.23, no.4, pp.1001-1014, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 4
  • Publication Date: 2012
  • Doi Number: 10.1007/s10845-010-0393-4
  • Journal Name: JOURNAL OF INTELLIGENT MANUFACTURING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1001-1014
  • Keywords: Unconstrained optimization, Constrained optimization, Mechanical design problems, Artificial bee colony, PARTICLE SWARM OPTIMIZATION, CONSTRAINED OPTIMIZATION, EVOLUTIONARY ALGORITHMS
  • Erciyes University Affiliated: Yes

Abstract

Engineering design problems are generally large scale or nonlinear or constrained optimization problems. The Artificial Bee Colony (ABC) algorithm is a successful tool for optimizing unconstrained problems. In this work, the ABC algorithm is used to solve large scale optimization problems, and it is applied to engineering design problems by extending the basic ABC algorithm simply by adding a constraint handling technique into the selection step of the ABC algorithm in order to prefer the feasible regions of entire search space. Nine well-known large scale unconstrained test problems and five well-known constrained engineering problems are solved by using the ABC algorithm and the performance of ABC algorithm is compared against those of state-of-the-art algorithms.