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Paper VII.1

Use of Genetic Algorithms in a Computer System for a Multi Objective Engineering Problem

J.C. Miles, J.N. Hooper and J. Bradshaw

Division of Civil Engineering, School of Engineering, University of Wales Cardiff, Wales

doi:10.4203/ccp.16.7.1

J.C. Miles, J.N. Hooper, J. Bradshaw, "Use of Genetic Algorithms in a Computer System for a Multi Objective Engineering Problem", in B.H.V. Topping, A.I. Khan, (Editors), "Neural Networks & Combinatorial Optimization in Civil & Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 137-145, 1993. doi:10.4203/ccp.16.7.1

Abstract

A genetic algorithm has been incorporated into a larger KBS. The genetic algorithm is required to perform quickly and reliably. An investigation into the relative merits of permutation search as opposed to genetic algorithms is described. Also the use of a new method of handling fitnesses within genetic algorithms is described and its merits relative to existing methods is discussed.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 16 NEURAL NETWORKS & COMBINATORIAL OPTIMIZATION IN CIVIL & STRUCTURAL ENGINEERING Edited by: B.H.V. Topping and A.I. Khan Paper VII.1 Use of Genetic Algorithms in a Computer System for a Multi Objective Engineering Problem J.C. Miles, J.N. Hooper and J. Bradshaw Division of Civil Engineering, School of Engineering, University of Wales Cardiff, Wales doi:10.4203/ccp.16.7.1 purchase the full-text of this paper Full Bibliographic Reference for this paper J.C. Miles, J.N. Hooper, J. Bradshaw, "Use of Genetic Algorithms in a Computer System for a Multi Objective Engineering Problem", in B.H.V. Topping, A.I. Khan, (Editors), "Neural Networks & Combinatorial Optimization in Civil & Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 137-145, 1993. doi:10.4203/ccp.16.7.1 Abstract A genetic algorithm has been incorporated into a larger KBS. The genetic algorithm is required to perform quickly and reliably. An investigation into the relative merits of permutation search as opposed to genetic algorithms is described. Also the use of a new method of handling fitnesses within genetic algorithms is described and its merits relative to existing methods is discussed. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £34 +P&P)
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