A survey of many-objective optimisation in search-based software engineering

被引:58
|
作者
Ramirez, Aurora [1 ]
Raul Romero, Jose [1 ]
Ventura, Sebastian [1 ]
机构
[1] Univ Cordoba, Dept Comp Sci & Numer Anal, E-14071 Cordoba, Spain
关键词
Search-based software engineering; Many-objective optimisation; Multi-objective optimisation; Evolutionary algorithms; Literature survey; EVOLUTIONARY ALGORITHMS; FEATURE-SELECTION; !text type='JAVA']JAVA[!/text] FRAMEWORK; MODEL; INTEGRATION; DIVERSITY;
D O I
10.1016/j.jss.2018.12.015
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Search-based software engineering (SBSE) is changing the way traditional software engineering (SE) activities are carried out by reformulating them as optimisation problems. The natural evolution of SBSE is bringing new challenges, such as the need of a large number of objectives to formally represent the many decision criteria involved in the resolution of SE tasks. This suggests that SBSE is moving towards many-objective optimisation, an emerging area that provides advanced techniques to cope with high dimensional optimisation problems. To analyse this phenomenon, this paper surveys relevant SBSE literature focused on the resolution of many-objective problems. From the gathered knowledge, current limitations regarding problem formulation, algorithm selection, experimental design and industrial applicability are discussed. Through the analysis of observed trends, this survey provides a historical perspective and future lines of research concerning the adoption of many-objective optimisation within SBSE. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:382 / 395
页数:14
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