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Research at St Andrews

Extending the ‘Open-Closed Principle’ to automated algorithm configuration

Research output: Contribution to journalArticle


Jerry Swan, Stephen Adriænsen, Adam David Barwell, Kevin Hammond, David White

School/Research organisations


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.


Original languageEnglish
JournalEvolutionary Computation
Early online date17 Dec 2018
StateE-pub ahead of print - 17 Dec 2018

    Research areas

  • Automated design of algorithms, Automatic programming, Programming by optimization, Metaheuristics, Functional programming, Ant programming, Search based software engineering, Systems self assembly

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ID: 257273894