A hybrid knowledge base system and genetic algorithms for equipment selection

Abstract

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.