Extending the "Open-Closed Principle" to Automated Algorithm Configuration

Jerry Swan, Steven Adriænsen, Adam D. Barwell, Kevin Hammond, David R. White
2018 Evolutionary Computation  
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 this paper, we identify shared state as the inhibitor of greater automation in
more » ... configuration. To solve this problem, we introduce the Automated Open Closed Principle (AOCP), which lists design requirements supporting reuse of algorithm frameworks and automated assembly of 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.
doi:10.1162/evco_a_00245 fatcat:v4643lke6jd5bamqkqgaib6x2i