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The use of computer communication networks has been rapidly increasing to 1) share expensive hardware and software resources, and 2) provide access to main systems from distant locations. The reliability and the cost of these systems are important considerations that are largely determined by network topology. Network topology consists of nodes and the links between nodes. The selection of optimal network topology is an NP-hard combinatorial problem so that the classical enumeration based methods grow exponentially with network size. In this study, a heuristic search algorithm inspired by evolutionary methods is presented to solve the all-terminal network design problem when considering cost and reliability. The genetic algorithm heuristic is considerably enhanced over conventional implementations to improve effectiveness and efficiency. This general optimization approach is shown to be computationally efficient and highly effective on a large suite of test problems with search spaces up to 2 × 10 90 .

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