Ant colony algorithm for construction resource leveling

被引：0
|
作者：
Kuang, Ya-Ping [1 ,2 ]
Xiong, Ying [3 ]
Zhang, Meng-Fang [4 ]
机构：
[1] College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310027, China
[2] School of Economics and Management, Tongji University, Shanghai 200092, China
[3] Hangzhou Engineering Consulting Center, Hangzhou 310006, China
[4] School of Architecture Engineering, Zhejiang University of Technology, Hangzhou 310014, China
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2008年 / 42卷 / 07期
关键词：
Scheduling algorithms - Artificial intelligence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An ant colony algorithm (ACO) was proposed to make a scientific plan in order to organize and utilize resources reasonably and raise the profit of construction project. The algorithm used serial schedule generation scheme (SSGS) to generate a feasible schedule and employed ACO to search the optimal schedule. The heuristic information was designed according to the characteristics of construction resource leveling. The parameters of the algorithm were set by trial and error with an example. Results verified the usefulness of the algorithm for construction resource leveling. Compared with enumeration, the algorithm produced the same global optimal solution with better searching efficiency, and a significant convergence occurs without much fluctuation.
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页码：1194 / 1198
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