Intermittent water systems suffer from several drawbacks such as unfair distribution among users, low reliability and poor water quality. Given limited water and financial resources, making decisions for improving intermittent water supply (IWS) becomes a complex process. The paths to continuous supply are a priori undefined, however, the provision of efficient service is crucial. In the scientific literature, limited research addresses how to improve intermittent systems, to enhance the current service while transitioning to continuous supply. A Multi-Objective Optimization (MOO) tool using a Genetic Algorithm has been developed to assist in investment decision-making. This approach uses multiple cost-effective intervention options to maximize equity and reliability while minimizing cost implications in an IWS system. The costs in such interventions include expenditure on pipe replacement, booster pump and elevated tank installation. The approach was first tested on a benchmark Hanoi synthetic network, and then applied to the water distribution network of Milagro (Ecuador). The developed tool reveals the extent to which equity and reliability can be driving objectives, and how they can be factored into decision-making. The application of the MOO tool in intermittent systems in order to improve existing distribution networks with strategic infrastructure addition can provide greater equity and reliability.