An efficient approach by adjusting bounds for heuristic optimization algorithms


SOFT COMPUTING, vol.23, no.13, pp.5199-5212, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 13
  • Publication Date: 2019
  • Doi Number: 10.1007/s00500-018-3327-2
  • Journal Name: SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.5199-5212
  • Keywords: Heuristic optimization, Accelerated particle swarm algorithm, Multi-pass turning operation model, Tension spring design problem, Welded beam design, PARTICLE SWARM OPTIMIZATION, MULTIPASS TURNING OPERATIONS, DESIGN OPTIMIZATION, STRUCTURAL DESIGN, GENETIC ALGORITHMS, SUPPORT, SEARCH
  • Eskisehir Osmangazi University Affiliated: Yes


In this article, a novel method is suggested for solving heuristic optimization problems. A pre-study was performed to define proper bounds. Different problems with these bounds were solved using genetic, accelerated particle swarm, and cuckoo search algorithms. Three different problems (multi-pass turning, welded beam design, and tension spring) were used as case studies. The results of the studies were compared with the earlier studies. As a result, the proposed method requires less computing time and has better objective function values compared to the solutions in the literature. The proposed method provides effective decision-making for operators and engineers dealing with different design and manufacturing environments in terms of cost and time.