蚁群优化算法
计算机科学
重新安置
数学优化
时间范围
启发式
蚁群
标杆管理
项目管理
元启发式
运筹学
设施选址问题
算法
工程类
数学
人工智能
系统工程
营销
业务
程序设计语言
作者
Pierrette P. Zouein,Sarah Kattan
标识
DOI:10.1080/01605682.2021.1920345
摘要
This paper presents an improved Ant Colony Optimization (ACOII) algorithm to solve the dynamic facility layout problem for construction sites. The algorithm uses a construction approach in building the layout solutions over time and uses a discrete dynamic search with heuristic info based on both relocation and flow costs to influence facilities’ placement in different time periods. The performance of ACOII is investigated using randomly generated data sets where the number of facilities and the number of time periods in the planning horizon vary to mimic what happens on a construction site over time. The experimental results show that ACOII is effective in solving the problem. A benchmarking study using instances from the literature showed promising results with improved solutions for all instances with very large number of facilities and periods.
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