A new hybrid differential evolution algorithm for the selection of optimal machining parameters in milling operations


Yildiz A. R.

APPLIED SOFT COMPUTING, vol.13, no.3, pp.1561-1566, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 3
  • Publication Date: 2013
  • Doi Number: 10.1016/j.asoc.2011.12.016
  • Journal Name: APPLIED SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1561-1566
  • Keywords: Milling, Hybrid optimization approach, Differential evolution, Receptor editing, GENETIC ALGORITHM, OPTIMIZATION PROBLEMS, DYNAMIC OPTIMIZATION, GLOBAL OPTIMIZATION, IMMUNE ALGORITHM, TAGUCHIS METHOD, DESIGN, SEARCH
  • Bursa Uludag University Affiliated: No

Abstract

This paper presents a novel hybrid optimization approach based on differential evolution algorithm and receptor editing property of immune system. The purpose of the present research is to develop a new optimization approach to solve optimization problems in the manufacturing industry. The proposed hybrid approach is applied to a case study for milling operations to show its effectiveness in machining operations. The results of the hybrid approach for the case study are compared with those of hybrid particle swarm algorithm, ant colony algorithm, immune algorithm, hybrid immune algorithm, genetic algorithm, feasible direction method and handbook recommendation. (C) 2012 Elsevier B. V. All rights reserved.