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Multi-drill path sequencing models: A comparative study

Author

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  • Vijay Rathod

    (Governement Polytechnic)

Abstract

In multi-hole drilling, optimization of the drill-path sequencing can lead to a significant reduction in machining time and eventually improves productivity in industries. Hence, the researchers have explored this domain and the similarity between the structure of the multi-hole drilling process and the traveling salesman problem. Wherein the prime intent is to seek the shortest possible path to minimize the traveling distance. Further, the researchers have used mainly three types of distance functions to model the travel distance of drill tools i.e., Euclidean, rectilinear, and Chebyshev distances. This paper aims to study these distance function models and compares their performances and effect on the drill-path sequences using test problems from the literature. The Simulated Annealing algorithm is utilized for the optimization of the drill-path sequences. It also discusses the abilities and shortcomings of these distance functions.

Suggested Citation

  • Vijay Rathod, 2023. "Multi-drill path sequencing models: A comparative study," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 554-570, March.
    • Handle: RePEc:spr:opsear:v:60:y:2023:i:1:d:10.1007_s12597-021-00562-0
    DOI: 10.1007/s12597-021-00562-0
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    References listed on IDEAS

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    1. Hu, Luoke & Liu, Ying & Peng, Chen & Tang, Wangchujun & Tang, Renzhong & Tiwari, Ashutosh, 2018. "Minimising the energy consumption of tool change and tool path of machining by sequencing the features," Energy, Elsevier, vol. 147(C), pages 390-402.
    2. Sunny Diyaley & Abhiraj Aditya & Shankar Chakraborty, 2020. "Optimization of the multi-hole drilling path sequence for concentric circular patterns," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 746-764, September.
    3. W. C. E. Lim & G. Kanagaraj & S. G. Ponnambalam, 2016. "A hybrid cuckoo search-genetic algorithm for hole-making sequence optimization," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 417-429, April.
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