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Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process

Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process

Goutam Kumar Bose, Pritam Pain, Supriyo Roy
Copyright: © 2019 |Pages: 15
ISBN13: 9781522582236|ISBN10: 1522582231|ISBN13 Softcover: 9781522586234|EISBN13: 9781522582243
DOI: 10.4018/978-1-5225-8223-6.ch014
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MLA

Bose, Goutam Kumar, et al. "Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process." Optimizing Current Strategies and Applications in Industrial Engineering, edited by Prasanta Sahoo, IGI Global, 2019, pp. 305-319. https://doi.org/10.4018/978-1-5225-8223-6.ch014

APA

Bose, G. K., Pain, P., & Roy, S. (2019). Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process. In P. Sahoo (Ed.), Optimizing Current Strategies and Applications in Industrial Engineering (pp. 305-319). IGI Global. https://doi.org/10.4018/978-1-5225-8223-6.ch014

Chicago

Bose, Goutam Kumar, Pritam Pain, and Supriyo Roy. "Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process." In Optimizing Current Strategies and Applications in Industrial Engineering, edited by Prasanta Sahoo, 305-319. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8223-6.ch014

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Abstract

Modern-day engineering is trending toward complex devices with high accuracy and precision while at the same time the workpiece materials are becoming harder and more complex alloys. Non-conventional machining helps to sustain industries in this challenging environment. Electric discharge machining is one such precision machining that can produce complex product with great accuracy. This machine can be utilized in the manufacturing of complicated shaped die for plastic molding, automobile parts, aerospace, and other applications. In solving real-world problems like engineering design, business planning, and network design, challenges are being faced due to highly non-linear data and limited resources like time and money. Optimization is the best choice to solve such practical problems efficiently. This chapter deals with the optimization of EDM process parameters using two different bio-inspired optimization algorithms, namely, artificial bee colony algorithm and whale optimization algorithm, for both single as well as multiple responses and compares the results.

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