Unconventional optimization for achieving well-informed design solutions for the automobile industry
Author:
Affiliation:
1. Computational Optimization and Innovation (COIN) Laboratory, Michigan State University, East Lansing, MI, USA
2. General Motors Vehicle Optimization Group, Warren, MI, USA
Funder
General Motors Corporation
Publisher
Informa UK Limited
Subject
Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications
Link
https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2019.1651310
Reference26 articles.
1. Colorni, Alberto, Marco Dorigo, and Vittorio Maniezzo. 1990. “Genetic Algorithms and Highly Constrained Problems: The Time-Table Case.” In Proceedings of the International Conference on Parallel Problem Solving from Nature (PPSN 1990), 55–59. Berlin: Springer-Verlag.
2. Corne, D. W., J. D. Knowles, and M. Oates. 2000. “The Pareto Envelope-Based Selection Algorithm for Multiobjective Optimization.” In Proceedings of the Sixth International Conference on Parallel Problem Solving from Nature (PPSN-VI), 839–848. Berlin: Springer-Verlag.
3. A fast and elitist multiobjective genetic algorithm: NSGA-II
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