An optimal construction resource leveling scheduling simulation model

Abstract

To meet the physical limits of construction resources, to avoid day-to-day fluctuation in resource demands, and to maintain an even flow of application for construction resources, resource leveling is needed in the construction industry. Traditional resource leveling models assume activity durations to be deterministic. Nevertheless, activity duration may be uncertain, owing to variations in the overall environment, such as weather, site congestion, and productivity level. A new optimal construction resource leveling model is proposed in this paper, in which the combinative effects of both uncertain activity duration and resource leveling are taken into consideration. Monte Carlo simulation is used to model the uncertainties of activity duration. A searching technique using genetic algorithms (GAs) is then adopted to search for the impact of uncertain activity durations on the probabilistic optimal resource leveling indices. The model can effectively provide probabilistic optimal resource leveling indices for multiple construction resources subjected to the objective of resource leveling, and the impact of influence factors on the probabilistic resource-leveling scheduling problems.Key words: resource leveling, genetic algorithms, simulation, probabilistic scheduling.