1. A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems
- Author
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Nantiwat Pholdee, Betül Sultan Yıldız, Ali Rıza Yıldız, Sujin Bureerat, Sadiq M. Sait, Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü., Yıldız, Betül Sultan, Yıldız, Ali Rıza, F-7426-2011, AAL-9234-2020, and AAH-6495-2019
- Subjects
0209 industrial biotechnology ,Mathematical optimization ,Design ,Computer science ,02 engineering and technology ,Learning algorithms ,Surface grinding process ,Structural optimization ,Simulated annealing ,Ant colony optimization ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,Optimal machining parameters ,General Materials Science ,Milling operations ,Multiobjective optimization ,Optimization of process parameters ,Millingdesign ,Artificial bee colony algorithms ,Optimization algorithm ,Simulated annealing algorithms ,Mechanical Engineering ,Particle swarm optimization ,Cutting Process ,Chatter ,Turning ,Manufacture ,Harris hawks algorithm ,Genetic algorithms ,Nelder mead ,Nelder meads ,Memetic agorithms ,Genetic algorithm ,Mechanics of Materials ,Particle swarm optimization algorithm ,020201 artificial intelligence & image processing ,Global optimization ,Gravitational search algorithms ,Nelder–Mead method ,Differential evolution ,Hybrid optimization ,Milling (machining) ,Materials science, characterization & testing ,Teaching-learning-based optimizations - Abstract
In this paper, a novel hybrid optimization algorithm (H-HHONM) which combines the Nelder-Mead local search algorithm with the Harris hawks optimization algorithm is proposed for solving real-world optimization problems. This paper is the first research study in which both the Harris hawks optimization algorithm and the H-HHONM are applied for the optimization of process parameters in milling operations. The H-HHONM is evaluated using well-known benchmark problems such as the three-bar truss problem, cantilever beam problem, and welded beam problem. Finally, a milling manufacturing optimization problem is solved for investigating the performance of the H-HHONM. Additionally, the salp swarm algorithm is used to solve the milling problem. The results of the H-HHONM for design and manufacturing problems solved in this paper are compared with other optimization algorithms presented in the literature such as the ant colony algorithm, genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm, artificial bee colony algorithm, teaching learning-based optimization algorithm, cuckoo search algorithm, multi-verse optimization algorithm, Harris hawks optimization optimization algorithm, gravitational search algorithm, ant lion optimizer, moth-flame optimization algorithm, symbiotic organisms search algorithm, and mine blast algorithm. The results show that H-HHONM is an effective optimization approach for optimizing both design and manufacturing optimization problems.
- Published
- 2019