Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem

During our earlier research, it was recognised that in order to be successful with an indirect genetic algorithm approach using a decoder, the decoder has to strike a balance between being an optimiser in its own right and finding feasible solutions. Previously this balance was achieved manually. He...

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Main Authors: Aickelin, Uwe, Dowsland, Kathryn
Format: Article
Language:English
Published: 2002
Subjects:
Online Access:https://eprints.nottingham.ac.uk/615/
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author Aickelin, Uwe
Dowsland, Kathryn
author_facet Aickelin, Uwe
Dowsland, Kathryn
author_sort Aickelin, Uwe
building Nottingham Research Data Repository
collection Online Access
description During our earlier research, it was recognised that in order to be successful with an indirect genetic algorithm approach using a decoder, the decoder has to strike a balance between being an optimiser in its own right and finding feasible solutions. Previously this balance was achieved manually. Here we extend this by presenting an automated approach where the genetic algorithm itself, simultaneously to solving the problem, sets weights to balance the components out. Subsequently we were able to solve a complex and non-linear scheduling problem better than with a standard direct genetic algorithm implementation.
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spelling nottingham-6152021-05-31T14:47:49Z https://eprints.nottingham.ac.uk/615/ Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem Aickelin, Uwe Dowsland, Kathryn During our earlier research, it was recognised that in order to be successful with an indirect genetic algorithm approach using a decoder, the decoder has to strike a balance between being an optimiser in its own right and finding feasible solutions. Previously this balance was achieved manually. Here we extend this by presenting an automated approach where the genetic algorithm itself, simultaneously to solving the problem, sets weights to balance the components out. Subsequently we were able to solve a complex and non-linear scheduling problem better than with a standard direct genetic algorithm implementation. 2002 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/615/1/02heur_igamall.pdf Aickelin, Uwe and Dowsland, Kathryn (2002) Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem. Journal of Heuristics, 8 (5). pp. 503-514. Genetic algorithms combinatorial optimisation heuristics scheduling http://www.springerlink.com/content/njmmum0cuh6xc92l/fulltext.pdf
spellingShingle Genetic algorithms
combinatorial optimisation
heuristics
scheduling
Aickelin, Uwe
Dowsland, Kathryn
Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title_full Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title_fullStr Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title_full_unstemmed Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title_short Enhanced Direct and Indirect Genetic Algorithm Approaches for a Mall Layout and Tenant Selection Problem
title_sort enhanced direct and indirect genetic algorithm approaches for a mall layout and tenant selection problem
topic Genetic algorithms
combinatorial optimisation
heuristics
scheduling
url https://eprints.nottingham.ac.uk/615/
https://eprints.nottingham.ac.uk/615/