A review and evaluation of multi and many-objective optimization: Methods and algorithms
<p>Most optimization problems naturally have several objectives, usually in conflict with each other. The problems with two or three objective functions are referred to as Multi-Objective Problems (MOP). However, many real-world applications often involve four or more objectives, which are com...
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Global Journal of Ecology - Peertechz Publications,
2022-11-09.
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LEADER | 00000 am a22000003u 4500 | ||
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001 | peertech__10_17352_gje_000070 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Farzane Karami |e author |
700 | 1 | 0 | |a Alireza B Dariane |e author |
245 | 0 | 0 | |a A review and evaluation of multi and many-objective optimization: Methods and algorithms |
260 | |b Global Journal of Ecology - Peertechz Publications, |c 2022-11-09. | ||
520 | |a <p>Most optimization problems naturally have several objectives, usually in conflict with each other. The problems with two or three objective functions are referred to as Multi-Objective Problems (MOP). However, many real-world applications often involve four or more objectives, which are commonly recognized as many-objective optimization problems (MaOP). Multi and many-objective algorithms have a great application in engineering science. This study addresses a complete and updated review of the literature for multi and many-objective problems and discusses 32 more important algorithms in detail. Afterward, the ZDT and DLTZ benchmark problems for multi-objective test problems are reviewed. All methods have been studied under recent state-of-the-art quality measures. Moreover, we discuss the historical roots of multi-objective optimization, the motivation to use evolutionary algorithms, and the most popular techniques currently in use.</p> | ||
540 | |a Copyright © Farzane Karami et al. | ||
546 | |a en | ||
655 | 7 | |a Review Article |2 local | |
856 | 4 | 1 | |u https://doi.org/10.17352/gje.000070 |z Connect to this object online. |