The last few decades have witnessed a growing interest in adapting mathematicalmodels that mimic natural biological processes into engineering designalgorithms, thereby increasing the robustness and efficiency of these tools. Thepresent study employs a genetic algorithm in the optimal design/expansion of amulti-source water distribution system that simultaneously maximizes thehydraulic redundancy. Overall system reliability for a water distribution systemmay be characterized into three different levels: component reliability(probability of a particular component remaining in operation), topologicalreliability (probability of network remaining physically connected), andhydraulic reliability (probability of a network being able to supply a fixed setof flowrates at adequate pressures). There have been several attempts in the pastto incorporate system reliability into optimal design formulations. Themethodology proposed by Ormsbee and Kessler provided two levels of redundancy,topological and hydraulic. While the topological redundancy was satisfied thoughusing graph theory, the hydraulic redundancy was satisfied though a linearprogramming formulation. Although the linear programming formulation resulted ina powerful optimal design/expansion model that simultaneously maximized thehydraulic redundancy, the problem formulation is rigorous and does not readilyallow for handling multiple source systems. The present study is aimed ataddressing some of the difficulties associated with linear programmingformulation as well as the limitation for multi-source systems through thedevelopment of a general heuristic that employs the use of a genetic optimizationin the solution of a sequential set of sub-problems.