Optimal Design of Redundant Water Distribution Networks Using a Cluster of Workstations

A genetic algorithm (GA)-based method for the least-cost design of looped pipe networks for various levels of redundancy is presented in this paper. Redundancy constraints are introduced in the optimization model by considering the number of pipes assumed to be out of service at any one time. Using this approach, trade-off relationships between cost and redundancy are developed. The GA-based approach is computationally intensive, and implementations on a custom fault-tolerant distributed computing framework, called Vitri, are used to satisfy the computational requirements. The design methodology is applied to two water distribution networks of different sizes, and a comparison of the performance of the distributed GAs for the design problems is also presented. We conclude that a GA-based approach to obtaining cost-effective, redundant solutions for the least-cost design of looped pipe networks can be effectively used on a heterogeneous network of nondedicated workstations.