Managing a construction project is challenging because of cost, time, safety, and quality considerations. In the most projects, the cost of construction is one of the most critical aspect because material cost alone accounts for significant ratio of the total project. Therefore, the cost of construction materials should be controlled. In this study, we proposed the use of material requirements planning (MRP) to control the cost of construction materials. After determining the demand for the materials required for construction, we estimated both the quantity of materials required and time taken to deliver the materials to the construction site. Although economic order quantity models have been applied to analyze construction material costs, they do not accurately reflect concerns related to material cost. Therefore, we used the material supply chain model (construction logistics planning) to analyze material costs. To optimize MRP according to the current progress of a project, a novel approach combining the dragonfly algorithm (DA) and particle swarm optimization algorithm (PSO) was proposed. To verify the advanced searchability of the DA–PSO algorithm, the algorithm was compared with the gray wolf and the genetic algorithms.

由于成本，时间，安全性和质量方面的考虑，管理建筑项目具有挑战性。在大多数项目中，建设成本是最关键的方面之一，因为仅材料成本就占了整个项目的很大比例。因此，应控制建筑材料的成本。在这项研究中，我们建议使用材料需求计划（MRP）来控制建筑材料的成本。在确定对建筑所需材料的需求后，我们估算了所需材料的数量以及将材料运送到施工现场所花费的时间。尽管经济订单数量模型已用于分析建筑材料成本，但它们不能准确反映与材料成本有关的问题。所以，我们使用了物料供应链模型（建筑物流计划）来分析物料成本。为了根据项目的当前进度优化MRP，提出了一种结合蜻蜓算法（DA）和粒子群优化算法（PSO）的新方法。为了验证DA–PSO算法的高级可搜索性，将该算法与“灰太狼”算法和遗传算法进行了比较。