Dataset on a Benchmark for Equality Constrained Multi-objective Optimization

被引：2
|
作者：
Cuate, Oliver [1 ]
Uribe, Lourdes [2 ]
Lara, Adriana [2 ]
Schutze, Oliver [1 ,3 ]
机构：
[1] CINVESTAV IPN, Dept Comp Sci, Mexico City, DF, Mexico
[2] Inst Politecn Nacl, ESFM, Mexico City, DF, Mexico
[3] UAM Cuajimalpa, Mexico City, DF, Mexico
来源：
DATA IN BRIEF | 2020年 / 29卷
关键词：
Evolutionary computation; Multi-objective optimization; Equality constraints; Benchmarking;
D O I：
10.1016/j.dib.2020.105130
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
In this Data in Brief, we provide the source code for the equality constrained multi-objective optimization benchmark problems EqDTLZ 1-4 and EqIDTLZ 1-2 proposed in the research article "A Benchmark for Equality Constrained Multi-objective Optimization" [1]. Further, we provide the codes for the multi-objective evolutionary algorithms NSGA-II, NSGA-III, aNSGA-III, GDE3, MOEA/D/D and PPS and their numerical approximations on the above mentioned test functions. All codes are provided in Matlab using the PlatEMO classes version 2.0 in order to test different algorithms. (C) 2020 The Author(s). Published by Elsevier Inc.
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页数：22
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