Performance measures for dynamic multi-objective optimisation algorithms

被引：81
|
作者：
Helbig, Mande [1 ,2 ]
Engelbrecht, Andries P. [2 ]
机构：
[1] CSIR, Meraka Inst, ZA-0184 Pretoria, South Africa
[2] Univ Pretoria, Dept Comp Sci, ZA-0002 Pretoria, South Africa
来源：
INFORMATION SCIENCES | 2013年 / 250卷
关键词：
Dynamic multi-objective optimisation; Performance measure; FRONT GENETIC ALGORITHM; EVOLUTIONARY ALGORITHM; MEMETIC ALGORITHM; METRICS;
D O I：
10.1016/j.ins.2013.06.051
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
When algorithms solve dynamic multi-objective optimisation problems (DMOOPs), performance measures are required to quantify the performance of the algorithm and to compare one algorithm's performance against that of other algorithms. However, for dynamic multi-objective optimisation (DMOO) there are no standard performance measures. This article provides an overview of the performance measures that have been used so far. In addition, issues with performance measures that are currently being used in the DMOO literature are highlighted. (c) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码：61 / 81
页数：21
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