book chapter · IGI Global eBooks · 2017
Multi-Objective Evolutionary Algorithms
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Abstract
The primary objective in designing appropriate particle reinforced polyurethane composite which will be used as a mould material in soft tooling process is to minimize the cycle time of soft tooling process by providing faster cooling rate during solidification of wax/plastic component. This chapter exemplifies an effective approach to design particle reinforced mould materials by solving the inherent multi-objective optimization problem associated with soft tooling process using evolutionary algorithms. In this chapter, first a brief introduction of multi-objective optimization problem with the key issues is presented. Then, after a short overview on the working procedure of genetic algorithm, a well- established multi-objective evolutionary algorithm, namely NSGA-II along with various performance metrics are described. The inherent multi-objective problem in soft tooling process is demonstrated and subsequently solved using an elitist non-dominated sorting genetic algorithm, NSGA-II. Multi-objective optimization results obtained using NSGA-II are analyzed statistically and validated with real industrial application. Finally the fundamental results of this approach are summarized and various perspectives to the industries along with scopes for future research work are pointed out.
Cite this paper
Nandi, A. K., & Deb, K. (2017). Multi-Objective Evolutionary Algorithms. IGI Global eBooks, 185–229. https://doi.org/10.4018/978-1-5225-1798-6.ch008
Nandi, A. K., and Kalyanmoy Deb. “Multi-Objective Evolutionary Algorithms.” IGI Global eBooks, 2017, pp. 185–229, https://doi.org/10.4018/978-1-5225-1798-6.ch008.
Nandi, A. K., and Kalyanmoy Deb. 2017. “Multi-Objective Evolutionary Algorithms.” IGI Global eBooks: 185–229. https://doi.org/10.4018/978-1-5225-1798-6.ch008.
Nandi, A.K. and Deb, K. (2017) ‘Multi-Objective Evolutionary Algorithms’, IGI Global eBooks, pp. 185–229. Available at: https://doi.org/10.4018/978-1-5225-1798-6.ch008.
@incollection{nandi2017multi,
title = {{Multi-Objective Evolutionary Algorithms}},
author = {Nandi, A. K. and Deb, Kalyanmoy},
booktitle = {IGI Global eBooks},
pages = {185--229},
year = {2017},
doi = {10.4018/978-1-5225-1798-6.ch008}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.