Name
Title | ||
|---|---|---|
An Empirical Study of Meta- and Hyper-Heuristic Search for Multi-Objective Release Planning. |
Abstract | ||
|---|---|---|
A variety of meta-heuristic search algorithms have been introduced for optimising software release planning. However, there has been no comprehensive empirical study of different search algorithms across multiple different real-world datasets. In this article, we present an empirical study of global, local, and hybrid meta- and hyper-heuristic search-based algorithms on 10 real-world datasets. We find that the hyper-heuristics are particularly effective. For example, the hyper-heuristic genetic algorithm significantly outperformed the other six approaches (and with high effect size) for solution quality 85% of the time, and was also faster than all others 70% of the time. Furthermore, correlation analysis reveals that it scales well as the number of requirements increases.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3196831 | ACM Trans. Softw. Eng. Methodol. |
Keywords | Field | DocType |
Strategic release planning, hyper-heuristics, meta-heuristics | Software release life cycle,Search algorithm,Computer science,Theoretical computer science,Hyper-heuristic,Artificial intelligence,Empirical research,Correlation analysis,Machine learning,Genetic algorithm,Metaheuristic | Journal |
Volume | Issue | ISSN |
27 | 1 | 1049-331X |
Citations | PageRank | References |
4 | 0.39 | 51 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuanyuan Zhang | 1 | 600 | 17.33 |
| Mark Harman | 2 | 10264 | 389.82 |
| Gabriela Ochoa | 3 | 276 | 29.38 |
| Guenther Ruhe | 4 | 662 | 44.98 |
| Sjaak Brinkkemper | 5 | 2599 | 219.13 |