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Exploring genetic alternative concepts for FUELGEN

Exploring genetic alternative concepts for FUELGEN

Soper, Alan ORCID: 0000-0002-0901-9803 (1998) Exploring genetic alternative concepts for FUELGEN. New Review of Applied Expert Systems, 4. pp. 185-194. ISSN 1361-0244

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Abstract

This paper describes new crossover operators and mutation strategies for the FUELGEN system, a genetic algorithm which designs fuel loading patterns for nuclear power reactors. The new components are applications of new ideas from recent research in genetic algorithms. They are designed to improve the performance of FUELGEN by using information in the problem as yet not made explicit in the genetic algorithm's representation. The paper introduces new developments in genetic algorithm design and explains how they motivate the proposed new components.

Item Type: Article
Additional Information: [1] The New Review of Applied Expert Systems was subsequently known as the New Review of Applied Expert Systems and Emerging Technologies.
Uncontrolled Keywords: computer architecture, genetic algorithms, nuclear reactors, reactor refueling, trees (mathematics), FUELGEN expert system, expert systems
Subjects: Q Science > QC Physics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Science
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:00
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/359

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