Joint entropy and multi-objective evolutionary optimization of water distribution networks
Tanyimboh, Tiku T. and Czajkowska, Anna M. (2018) Joint entropy and multi-objective evolutionary optimization of water distribution networks. Water Resources Management. ISSN 0920-4741 (https://doi.org/10.1007/s11269-017-1888-y)
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Abstract
It is essential to consider resilience when designing any water distribution network and surrogate measures of resilience are used frequently as accurate measures often impose prohibitive computational demands in optimization algorithms. Previous design optimization algorithms based on flow entropy have essentially employed a single loading condition because the flow entropy concept formally has not been extended to multiple loading conditions in water distribution networks. However, in practice, water distribution networks must satisfy multiple loading conditions. The aim of the research was to close the gap between the prevailing entropy-based design optimization approaches based on one loading condition essentially and water distribution practice that must address multiple loading conditions. A methodology was developed and applied to a real-world water distribution network in the literature, based on the concept of the joint entropy of independent probability schemes. The results demonstrated that the critical loading conditions were design specific. In other words, the critical loading and operating conditions cannot readily be determined beforehand. Consequently, maximizing the joint entropy provided the most consistently competitive solutions in terms of the balance between cost and resilience. The results were derived using a penalty-free genetic algorithm with three objectives. Compared to previous research using flow entropy based on a single loading condition and two objectives, there was a substantial increase of 274% in the number of non-dominated solutions achieved.
ORCID iDs
Tanyimboh, Tiku T. ORCID: https://orcid.org/0000-0003-3741-7689 and Czajkowska, Anna M. ORCID: https://orcid.org/0000-0002-9978-8568;-
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Item type: Article ID code: 63023 Dates: DateEvent12 April 2018Published12 April 2018Published Online27 December 2017AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 24 Jan 2018 16:28 Last modified: 14 Nov 2024 01:11 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/63023