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The application of the ant colony optimization algorithm to the construction site layout planning problem

机译:蚁群优化算法在施工现场布局规划中的应用

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A good site layout is vital to ensure the safety of the working environment, and for effective and efficient operations. Moreover, it minimizes travel distance, decreases materials handling, and avoids the obstruction of materials and plant movement. Based on studies in the manufacturing industry, the cost of materials handling could be reduced by 20-60% if an appropriate facility layout is adopted. In designing a site layout, a planner will first position the key facilities that influence the method and sequence of construction, and then assign the remaining facilities in the available space that is left over. This process is similar to the positioning of facilities in the ant colony optimization (ACO) algorithm. The general principle of the ACO algorithm is to assign facilities to a location one by one, and the occupied locations are deleted from the location scope in the next assignment. In the study, ACO algorithm is employed to resolve the construction site layout planning problem in a hypothetical medium-sized construction project. By applying fuzzy reasoning and the entropy technique, the study calculates the closeness relationship between facilities, in which the optimal site layout is affected by the mutual interaction of facilities.
机译:良好的场地布局对于确保工作环境的安全以及有效的运营至关重要。此外,它使行进距离最小化,减少了物料搬运,并避免了物料阻塞和工厂移动。根据制造业的研究,如果采用适当的设施布局,则材料处理成本可以降低20-60%。在设计场地布局时,规划人员将首先放置影响施工方法和顺序的关键设施,然后在剩余的可用空间中分配其余设施。此过程类似于蚁群优化(ACO)算法中设施的定位。 ACO算法的一般原理是将设施逐个分配给一个位置,并在下一次分配中从位置范围中删除占用的位置。在研究中,采用ACO算法来解决假设的中型建筑项目中的工地布局规划问题。通过运用模糊推理和熵技术,计算出设施之间的亲密关系,其中设施的相互影响会影响到最佳的场地布置。

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