Ant Colony Optimization for Design of Water Distribution Systems
Ant Colony Optimization for Design of Water Distribution Systems
复制标题
配水系统设计的蚁群优化
DOI：
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复制
发表时间：
2003
期刊：
影响因子：
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通讯作者：
C. Tan
中科院分区：
文献类型：
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作者：
H. Maier;A. Simpson;A. Zecchin;W. Foong;Kuang Yeow Phang;Hsin Yeow Seah;C. Tan
在过去的十年中，进化方法，如遗传算法已被广泛用于水分配系统的优化设计和运行。最近，蚁群优化算法（ACOA），这是基于蚂蚁觅食行为的进化方法，已成功地应用于一些基准组合优化问题。在本文中，制定了一个配方，使ACOA用于配水系统的优化设计。该配方适用于两个基准配水系统优化问题，并与遗传算法（GAs）所获得的结果进行了比较。这项研究的结果表明，ACOA是一个有吸引力的替代气体的配水系统的优化设计，因为它们优于气体的两个案例研究认为无论是在计算效率和他们的能力，找到接近全球最优解。
During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the optimal design and operation of water distribution systems. More recently, ant colony optimization algorithms (ACOAs), which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to a number of benchmark combinatorial optimization problems. In this paper, a formulation is developed which enables ACOAs to be used for the optimal design of water distribution systems. This formulation is applied to two benchmark water distribution system optimization problems and the results are compared with those obtained using genetic algorithms (GAs). The findings of this study indicate that ACOAs are an attractive alternative to GAs for the optimal design of water distribution systems, as they outperformed GAs for the two case studies considered both in terms of computational efficiency and their ability to find near global optimal solutions.