A hybrid mechanism for optimizing construction simulation models

Simulation is a powerful tool for planning and scheduling highly repetitive tasks in a construction project. However, sensitivity analysis has to be utilized to find the best resource combination to execute the construction tasks. By performing the sensitivity analysis, various resource combinations can be evaluated in terms of their effects on the operation's production and cost. The results of the sensitivity analysis can assist project managers in planning effective resource assignments based on their goals, such as maximizing the system's production rate or minimizing the system's unit cost. However, it is time-consuming to conduct the sensitivity analysis if there are a large number of resource alternatives available. This paper proposes a hybrid mechanism that integrates heuristic algorithms and genetic algorithms to efficiently locate the best resource combination for the construction simulation optimization. Results show that this new hybrid mechanism not only locates the optimal solution but also reduces tremendous computational efforts.