Study on construction material allocation policies: A simulation optimization method

Abstract

Due to uncertainty in both demand and supply, material shortages are difficult to completely avoid. To reduce the effect on the schedule and cost performance of construction projects, managers should allocate limited material among activities effectively. Motivated by observations of construction practices, this paper investigates the integration of supply logistics and site logistics issues and develops a framework to model inventory replenishment and allocation decisions jointly. On the basis of the activity feature information (e.g., schedule, cost, and demand), we propose five allocation policies to support the integrated inventory management process: schedule-based, cost-based, demand-based, schedule-cost-based, and schedule-demand-based policies. Meanwhile, a genetic algorithm (GA)-based simulation optimization method is utilized to solve the integrated inventory model and find the optimal inventory level under a given allocation policy. Based on a large set of fictitious project networks with different path difference (PD), a computational analysis is conducted to make detailed interpolicy comparisons. It is shown that for a project network with a small (or large) PD value, the schedule-based (or schedule-cost-based) policy is the most appropriate choice.