SOFT COMPUTING, cilt.23, sa.13, ss.5199-5212, 2019 (SCI-Expanded)
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.