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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Main Authors: Farzane Karami (Author), Alireza B Dariane (Author)
Format: Book
Published: Global Journal of Ecology - Peertechz Publications, 2022-11-09.
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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.