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Optimization of Construction Material Cost through Logistics Planning Model of Dragonfly Algorithm - Particle Swarm Optimization

机译:蜻蜓算法物流规划模型优化施工材料成本 - 粒子群优化

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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.
机译:由于成本,时间,安全和质量考虑,管理建设项目是具有挑战性的。在大多数项目中,建设成本是最关键的方面之一,因为物质成本仅占总项目的显着比率。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。在确定建筑所需材料的需求之后,我们估计所需材料的数量,以将材料传送到施工现场。虽然已经应用了经济秩序数量模型来分析施工材料成本,但它们不准确反映与材料成本相关的疑虑。因此,我们使用了材料供应链模型(建筑物流规划)来分析材料成本。为了根据项目的当前进度优化MRP,提出了一种组合蜻蜓算法(DA)和粒子群优化算法(PSO)的新方法。为了验证DA-PSO算法的高级搜索性,将该算法与灰狼和遗传算法进行比较。

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