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

被引:57
作者
Lam, Ka-Chi [1 ]
Ning, Xin [1 ]
Ng, Thomas [2 ]
机构
[1] City Univ Hong Kong, Dept Bldg & Construct, Hong Kong, Hong Kong, Peoples R China
[2] Univ Hong Kong, Dept Civil Engn, Hong Kong, Hong Kong, Peoples R China
关键词
ACO algorithm; site layout; heuristic; closeness relationship;
D O I
10.1080/01446190600972870
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:359 / 374
页数:16
相关论文
共 43 条
[31]   A hybrid ant colony optimization algorithm for drone-based cooperative EV routing problem with simultaneously delivery and pickup [J].
Yang, Yongjian ;
Feng, Tianjiao ;
Luo, Chenyu ;
Li, Chenglong ;
Wang, Jun ;
Xiong, Yuning .
ANNALS OF OPERATIONS RESEARCH, 2025,
[32]   Modelling the effect of multi-stakeholder interactions on construction site layout planning using agent-based decentralized optimization [J].
Song, Xiaoling ;
Pena-Mora, Feniosky ;
Shen, Charles ;
Zhang, Zhe ;
Xu, Jiuping .
AUTOMATION IN CONSTRUCTION, 2019, 107
[33]   Robotic disassembly line balancing problem: A mathematical model and ant colony optimization approach [J].
Cil, Zeynel Abidin ;
Mete, Suleyman ;
Serin, Faruk .
APPLIED MATHEMATICAL MODELLING, 2020, 86 :335-348
[34]   Application of 4D for dynamic site layout and management of construction projects [J].
Ma, ZY ;
Shen, QP ;
Zhang, JP .
AUTOMATION IN CONSTRUCTION, 2005, 14 (03) :369-381
[35]   JS']JSWA: An Improved Algorithm for Grid Workflow Scheduling using Ant Colony Optimization [J].
Niazmand, Emetis ;
Delavar, Arash Ghorbannia ;
Bayrampoor, Javad ;
Boroujeni, Ali Reza Khalili .
JOURNAL OF MATHEMATICS AND COMPUTER SCIENCE-JMCS, 2013, 6 (04) :315-331
[36]   Metaheuristic (Ant Colony Optimization) Algorithm-Based Optimization of a Circular Shaped Patch Antenna for Medical Purposes [J].
D. S. Mahesh ;
K. B. Naveen .
SN Computer Science, 5 (7)
[37]   Dynamic construction material layout planning optimization model by integrating 4D BIM [J].
Cheng, Min-Yuan ;
Chang, Nai-Wen .
ENGINEERING WITH COMPUTERS, 2019, 35 (02) :703-720
[38]   Grid-based construction site layout planning with Particle Swarm Optimisation and Travel Path Distance [J].
Benjaoran, Vacharapoom ;
Peansupap, Vachara .
CONSTRUCTION MANAGEMENT AND ECONOMICS, 2020, 38 (08) :673-688
[39]   Optimization analysis of node energy consumption in wireless sensor networks based on improved ant colony algorithm [J].
Wang, Long ;
Luo, Yiqun ;
Yan, Hongyan .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2024, 64
[40]   A Novel Hybrid Heuristic Based on Ant Colony Algorithm for Solving Multi-product Inventory Routing Problem [J].
Oudouar, Fadoua ;
Zaoui, El Miloud .
ADVANCED TECHNOLOGIES FOR HUMANITY, 2022, 110 :519-529