Optimal Fleet Selection for Earthmoving Operations

Earthmoving operations often involve a large number of specially designed equipment with significant purchasing/leasing prices, high operating and maintenance costs. Hence, choosing the right fleet is a major concern from the construction planners’ point of view. This paper presents a methodology that combines discrete-event simulation and optimization to solve the optimal fleet selection problem for earthmoving operations. Two optimization objectives are formulated and solved using the proposed framework and a genetic algorithm: minimization of Total Cost of Ownership (TCO) and maximization of productivity. Further, a two-stage rating scheme is introduced to arrange the fleet configurations so that the optimization algorithm converges to a fleet with better second-stage performance while the first-stage performance remains at the same level. The case study shows that the proposed mechanism can effectively allocate an optimal equipment combination for earthmoving operations and hence serve as an efficient tool for construction management.