Selecting earthmoving equipment fleets using genetic algorithms

This paper presents an application of simulation optimization in construction utilizing genetic algorithms. The paper focuses on the use of genetic algorithms (GAs) as a tool for optimizing the total cost of earthmoving operations accounting for available equipment models to contractors and their corresponding quantities. The developed genetic algorithm has a powerful computational utility that increases its efficiency. The fitness of generated chromosomes is calculated utilizing a simulation engine dedicated for earthmoving operations which is dynamically linked to the developed genetic algorithm. The impact of the algorithm´s control parameters on its conversion is also examined. A numerical example is presented to illustrate the capabilities of the developed algorithm in selecting near-optimum fleet configurations.