Paper Info
Title
Mutation With Local Searching And Elite Inheritance Mechanism In Multi-Objective Optimization Algorithm: A Case Study In Software Product Line
Abstract
An effective method for addressing the configuration optimization problem (COP) in Software Product Lines (SPLs) is to deploy a multi-objective evolutionary algorithm, for example, the state-of-the-art SATIBEA. In this paper, an improved hybrid algorithm, called SATIBEA-LSSF, is proposed to further improve the algorithm performance of SATIBEA, which is composed of a multi-children generating strategy, an enhanced mutation strategy with local searching and an elite inheritance mechanism. Empirical results on the same case studies demonstrate that our algorithm significantly outperforms the state-of-the-art for four out of five SPLs on a quality Hypervolume indicator and the convergence speed. To verify the effectiveness and robustness of our algorithm, the parameter sensitivity analysis is discussed and three observations are reported in detail.
Year
DOI
Venue
2019
10.1142/S0218194019500426
INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING
Keywords
Field
DocType
Software product lines, search-based software engineering, multi-objective evolutionary algorithms, constraint solving
Data mining,Evolutionary algorithm,Effective method,Computer science,Multi-objective optimization,Software,Software product line,Optimization problem,Search-based software engineering
Journal
Volume
Issue
ISSN
29
9
0218-1940
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Kai Shi1113.47
Huiqun Yu210621.74
Guisheng Fan39125.45
Jianmei Guo439022.80
Liqiong Chen57519.61
Xingguang Yang602.03
Huaiying Sun7102.51