Name
Abstract | ||
|---|---|---|
Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of a metaheuristic for a given problem has historically been a manually intensive process based on experience, experimentation, and reasoning by metaphor. More recently, there has been interest in automating the process of algorithm configuration. In this paper, we identify shared state as an inhibitor of progress for such automation. To solve this problem, we introduce the Automated Open Closed Principle (AOCP), which stipulates design requirements for unintrusive reuse of algorithm frameworks and automated assembly of algorithms from an extensible palette of components. We demonstrate how the AOCP enables a greater degree of automation than previously possible via an example implementation. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1162/evco_a_00245 | Evolutionary computation |
Keywords | Field | DocType |
Ant Programming,Automated Design of Algorithms,Automatic Programming,Functional Programming,Metaheuristics,Programming by Optimization,Search Based Software Engineering,Systems Self Assembly | Open/closed principle,Mathematical optimization,Functional programming,Algorithm configuration,Optimization algorithm,Mathematics,Metaheuristic,Automatic programming,Search-based software engineering | Journal |
Volume | Issue | ISSN |
27 | SP1 | 1530-9304 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jerry Swan | 1 | 196 | 19.47 |
| Steven Adriaensen | 2 | 15 | 2.44 |
| Adam D. Barwell | 3 | 18 | 3.91 |
| Kevin Hammond | 4 | 175 | 17.81 |
| David L. White | 5 | 48 | 5.51 |