Comparative Study of Multi-hole Drill Path Optimization using Evolutionary Algorithms-Reference-Cited by-同舟云学术

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Comparative Study of Multi-hole Drill Path Optimization using Evolutionary Algorithms

Published:2022-12-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
language:
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Author:

Rathod V. P.¹,Yadav O. P.²,Rathore A.P. S.³

Affiliation:

1. Government Polytechnic,Department of Mechanical Engineering,Ratnagiri,India

2. North Dakota State University,Department of Industrial and Manufacturing Engineering,Fargo,USA

3. Malaviya National Institute of Technology,Department of Mechanical Engineering,Jaipur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9989527/9989519/09989689.pdf?arnumber=9989689

Reference16 articles.

1. Genetic Algorithms in Search, Optimization, and Machine Learning;goldberg;Addison-Wesley Publishing Inc,1989

2. Swine Influenza Model Based Optimization using seasonal flu shots (SIMBO-SS)

3. Ant colony optimization theory: A survey

4. Particle swarm optimization

5. Determination of the optimal drill path sequence using bat algorithm and analysis of its optimization performance

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Canonical Form of the TLBO for Multi-Hole Drilling;2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM);2023-12-18

2. Discrete Teaching Learning-Based Optimization for Multi-Hole Drilling;2023 2nd International Conference for Innovation in Technology (INOCON);2023-03-03

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