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Mathematical Problems in Engineering
Volume 2015, Article ID 162712, 15 pages
http://dx.doi.org/10.1155/2015/162712
Research Article

A Study on Many-Objective Optimization Using the Kriging-Surrogate-Based Evolutionary Algorithm Maximizing Expected Hypervolume Improvement

Institute of Fluid Science, Tohoku University, Sendai 980-8577, Japan

Received 25 August 2014; Revised 13 January 2015; Accepted 13 January 2015

Academic Editor: Yudong Zhang

Copyright © 2015 Chang Luo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Chang Luo, Koji Shimoyama, and Shigeru Obayashi, “A Study on Many-Objective Optimization Using the Kriging-Surrogate-Based Evolutionary Algorithm Maximizing Expected Hypervolume Improvement,” Mathematical Problems in Engineering, vol. 2015, Article ID 162712, 15 pages, 2015. https://doi.org/10.1155/2015/162712.