@inproceedings{4f6f1740ee83420c99574c0a3d2ea3c9,
title = "Comparison of multiple objective genetic algorithms for parallel machine scheduling problems",
abstract = "Many multiple objective genetic algorithms have been developed to approximate the efficient frontier of solutions for multiple objective optimization problems. However, only a limited number of comparison studies have been performed on practical problems. One of the reasons for this may be the lack of commonly accepted measures to compare the solution quality of sets of approximately optimal solutions. In this paper, we perform an extensive set of experiments to quantitatively compare the solutions of two competing algorithms for a bi-criteria parallel machine-scheduling problem.",
author = "{Matthew Carlyle}, W. and Bosun Kim and John Fowler and Esma Gel",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; 1st International Conference on Evolutionary Multi-Criterion Optimization, EMO 2001 ; Conference date: 07-03-2001 Through 09-03-2001",
year = "2001",
doi = "10.1007/3-540-44719-9_33",
language = "English (US)",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "472--485",
editor = "Eckart Zitzler and Lothar Thiele and Kalyanmoy Deb and Coello, {Carlos A. Coello} and David Corne",
booktitle = "Evolutionary Multi-Criterion Optimization - 1st International Conference, EMO 2001, Proceedings",
}