Robust water system design with commercial intelligent search optimizers

Intelligent-search-based optimizers have shown promise in providing improve d links between analysis and design. Genetic-algorithm-based optimizers are often used, but other heuristic methods, such as tabu search, have also be en used with good results. A major impediment to using heuristic search met hods has been the lack of user-friendly, commercially available software. T his is no longer the case due to the availability of several commercial int elligent-search-based optimizers. Robust analysis and optimization of a wat er distribution network is demonstrated with four commercial optimizers. Th e hydraulic analysis is performed with WinPipes.EXE, a Windows program base d on the EPANET source code. The method is demonstrated by optimizing the N ew York City Water Supply Tunnel problem, and by the optimal design of a 15 -loop, Almos water distribution system. The method is robust because it use s reliable and efficient commercial optimizers, a popular pipe network solv er, and constraint penalties to meet the multiple goals of a reliable, low- cost water distribution system, capable of meeting maximum hour demands and fire flow demands.