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Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Entropy based design of "Anytown" water distribution network

Prasad, TD and Tanyimboh, Tiku (2008) Entropy based design of "Anytown" water distribution network. In: Water Distribution Systems Analysis 2008, 2008-08-17 - 2008-08-20.

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Abstract

Design optimization of looped water distribution networks has been a thoroughly researched problem for the last four decades. However, very few works have been published dealing with the optimal design of complex water distribution networks containing various network elements, such as the "Anytown" water distribution network. The central theme of the present work is to develop a design model satisfying the following requirements: (i) GAs are developed for unconstrained optimization problems. That is, they have difficulty in handling constraints in a constrained optimization problem, so the solution strategy should reduce the number of constraints that must be handled by GA and (ii) existing/new tanks should utilize their full operational capacity and exhibit good recirculation capabilities such that water quality problems are reduced. Keeping these two aspects in mind a new optimization model including a tank design procedure, which requires complete description of a tank’s parameters, is proposed. Minimization of Network cost and maximization of flow entropy are considered as the two objectives. A multi-objective genetic algorithm, namely NSGA-II, is used and the efficacy of the proposed model is demonstrated. It will be shown that the flow entropy could be used as a surrogate reliability measure and that it alleviates drawbacks of some of the other surrogate measures such as resilience index. New results obtained for the "Anytown" network show that the model manages to find better solutions and satisfy all the constraints including pressure constraints in EPS.