Mutation with Local Searching and Elite Inheritance Mechanism in Multi-Objective Optimization Algorithm: A Case Study in Software Product Line
| Autor: | Kai Shi, Xingguang Yang, Guisheng Fan, Huaiying Sun, Jianmei Guo, Liqiong Chen, Huiqun Yu |
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| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
Computer Networks and Communications Computer science business.industry Search-based software engineering Evolutionary algorithm Computer Graphics and Computer-Aided Design Inheritance (object-oriented programming) Software Artificial Intelligence Product (mathematics) Mutation (genetic algorithm) Effective method Software product line business |
| Zdroj: | International Journal of Software Engineering and Knowledge Engineering. 29:1347-1378 |
| ISSN: | 1793-6403 0218-1940 |
| DOI: | 10.1142/s0218194019500426 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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