SIMULATION-BASED OPTIMIZATION OF EARTHMOVING OPERATIONS USING GENETIC ALGORITHM

Earthmoving operations are a fundamental part of heavy construction projects. From the project manager's point of view, understanding of both productivity and cost estimations is indispensable. Equipment selection is an important factor in the resulting productivity and cost of operations. Traditionally, the equipment selection is performed based on experience and rules of thumb. This paper presents a framework of simulation-based optimization of resource selection in earthmoving operations by integrating a discrete-event simulation platform with a genetic algorithm. The simulation engine evaluates the performance (fitness) of each equipment combination and the genetic algorithm searches for an optimal equipment configuration while considering a set of qualitative and quantitative decision variables which influence the performance of earthmoving operations. A prototype has been developed to demonstrate the applicability of the proposed framework. Pilot simulation runs show that this system can effectively locate a near optimal equipment combination for earthmoving operations. The proposed simulation optimization framework can hence serve as an efficient tool for project management in fleet selection.