To read this content please select one of the options below:

A hybrid knowledge base system and genetic algorithms for equipment selection

SHAMIL NAOUM (South Bank University, School of Construction, Wandsworth Road, London SW8 2J2, UK)
ALI HAIDAR (South Bank University, School of Construction, Wandsworth Road, London SW8 2J2, UK)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 1 January 2000

137

Abstract

This paper describes the development of a hybrid knowledge base system and genetic algorithms to select the optimum excavating and haulage equipment in opencast mining. The knowledge base system selects the equipment in broad categories based on the geological, technical and environmental characteristics of the mine. To further identify the make, size and number of each piece of equipment that minimizes the total cost of the operation, the problem is solved using the genetic algorithms mechanism. Results of four case studies are presented to show the validation of the developed system.

Keywords

Citation

NAOUM, S. and HAIDAR, A. (2000), "A hybrid knowledge base system and genetic algorithms for equipment selection", Engineering, Construction and Architectural Management, Vol. 7 No. 1, pp. 3-14. https://doi.org/10.1108/eb021128

Publisher

:

MCB UP Ltd

Copyright © 2000, MCB UP Limited

Related articles