Skip to main content

A Design Framework for Metaheuristics

Johnson, Colin G. (2008) A Design Framework for Metaheuristics. Artificial Intelligence Review, 29 (2). pp. 163-178. ISSN 0269-2821. (doi:10.1007/s10462-009-9113-x) (KAR id:24137)

PDF
Language: English
Download (227kB) Preview
[thumbnail of design_framework_johnson.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL
http://dx.doi.org/10.1007/s10462-009-9113-x

Abstract

This paper is concerned with taking an engineering approach towards the application of metaheuristic problem solving methods, i.e. heuristics that aim to solve a wide variety of problems. How can a practitioner solve a problem using metaheuristic methods? What choices do they have, and how are these choices influenced by the problem at hand? Are there sensible universal choices which can be made, or are these choices always problem-dependent? The aim of this paper is to address questions such as these in the context of a (soft) engineering design framework for the application of metaheuristics. The aim of this framework is to make explicit the choices which a practitioner needs to make in applying these techniques, and to give some guidelines for how metaheuristics might be tuned to problems by considering different problem- and solution-types.

Item Type: Article
DOI/Identification number: 10.1007/s10462-009-9113-x
Uncontrolled keywords: Heuristics; Optimisation; Artificial Intelligence; Genetic Algorithms; Operational Research; Problem Solving
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:16 UTC
Last Modified: 16 Feb 2021 12:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/24137 (The current URI for this page, for reference purposes)
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
  • Depositors only (login required):

Downloads

Downloads per month over past year