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An efficient approach by adjusting bounds for heuristic optimization algorithms
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DOI：10.1007/s00500-018-3327-2.png)
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Abstract
En 中文
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.
Keywords:
Heuristic optimization
Accelerated particle swarm algorithm
Multi-pass turning operation model
Tension spring design problem
Welded beam design
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