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The construction industry remains the least sustainable area and largely involves the use of non-renewable resources. More importantly, the largest source of greenhouse gas emissions, emanate from conventional (non-green) buildings and the transport sector; contributing enormously to climate change. Although the importance of protecting the environment for future generation has been recognised by all major polluting countries of the world, many countries refuse to comply with all the conditions of environmental protocols because of the economic implications.

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In this paper the authors compare two optimization techniques, namely the Genetic Algorithm and the Particle Swarm Optimization for water distribution networks. The effectiveness of the two algorithms is tested on two benchmark water distribution networks namely, the New York City water supply tunnel system and the Hanoi water distribution network and a comparison of the two techniques is presented. Furthermore the two algorithms are applied to two local water distribution networks in Mauritius which is very old and no such study has been done before on these data. This study will be beneficial to the government for decision making more specific for water management of the island following the severe drought problems during the last three years.

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