Projects per year
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.
Original language | English |
---|---|
Pages (from-to) | 173-193 |
Number of pages | 21 |
Journal | Evolutionary Computation |
Volume | 27 |
Issue number | 1 |
Early online date | 17 Dec 2018 |
DOIs | |
Publication status | Published - 4 Mar 2019 |
Keywords
- Automated design of algorithms
- Automatic programming
- Programming by optimization
- Metaheuristics
- Functional programming
- Ant programming
- Search based software engineering
- Systems self assembly
Fingerprint
Dive into the research topics of 'Extending the ‘Open-Closed Principle’ to automated algorithm configuration'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Discovery: Pattern Discovery and Program: Discovery: Pattern Discovery and Program Shaping for Manycore Systems
Thomson, J. D. (PI), Hammond, K. (CoI) & Sarkar, S. (CoI)
1/07/17 → 31/12/20
Project: Standard