Otimização multiobjetivo de projetos de redes de distribuição de água

Abstract

O dimensionamento otimizado de sistemas de distribuição de águas tem originado centenas de trabalhos científicos nas últimas quatro décadas. Vários pesquisadores têm buscado encontrar uma metodologia capaz de dimensionar essas redes considerando diversos aspectos e incertezas características desse tipo de projeto. No entanto, os resultados das da maioria das metodologias desenvolvidas não podem ser aplicados na prática. O objetivo deste trabalho é elaborar uma metodologia de dimensionamento de redes de distribuição de água considerando um enfoque multiobjetivo. A metodologia desenvolvida considera três aspectos referentes ao projeto desses sistemas: custo; confiabilidade e perdas por vazamentos. Para tanto, empregou-se um método de otimização multiobjetivo baseado em algoritmos genéticos para a geração do conjunto de soluções não-dominadas e um método multicriterial para escolha da alternativa final. Para representar os objetivos do problema, foram testadas nove funções: custo, vazamentos, entropia, resiliência, tolerância à falha, expansibilidade, efeito do envelhecimento e resilientropia, sendo que sete destas são específicas para a representação da confiabilidade. Para se avaliar as alternativas geradas foi desenvolvido um modelo de análise hidráulica que fosse capaz de trabalhar com vazamentos e com demandas dependente da pressão. Os métodos escolhidos foram o The topic "Optimized design of water distribution systems" has generated hundreds of scientific publications in the last four decades. Several researchers have searched for a technology which would take into account a variety of aspects and uncertainties innate to the design of such networks. However, the results of most methodologies developed are not practical. The objective of this work is to develop a methodology for water distribution systems design that has a multiobjective focus. The methodology developed focuses in three aspects of the design of such systems: cost, reliability and losses by leaking. A multiobjective optimization method based on generic algorithms, generating a set of non-defined solutions, and a multi-criteria method for choosing the final alternative, was employed. Nine functions representing the objectives of the problem (method) were tested: cost, leakages, entropy, resilience, failure tolerance, expansibility, aging effect and resilienthropy, seven of which are specific to representing reliability. In order to evaluate the generated alternatives, a hydraulic analysis model, that could handle leakages and pressure dependent demands, was developed. The chosen methods were Nielsen's Hybrid, and the Gradient. Of all tested functions, resilientropy, originally proposed in this work, proved to be the one best adjusted to the formal concept of reliability, represented by the tolerance function. The results obtained by this methodology are promising, as they produced efficient distribution networks at the end of the simulations performed.

Calibração do Storm Water Management Model (SWMM) utilizando algoritmos evolucionários multiobjetivo

“…Escolha ou ordenação das soluções do problema (Formiga, 2005 A inclinação média do conjunto de soluções foi de 9,5%, que é próximo do valor de 10,9%, e a largura da bacia, que é um parâme-tro teórico sem grande representação física, ficou em torno de 750 m.…”

Optimal dimensioning model of water distribution systems

“…6) is the R-9 Network, a medium-size municipal network in Joao Pessoa city -Brazil, implemented by an urban water company in 1982, which consists of 53 nodes connected via 72 pipes and a reservoir. The input data for this problem are given in FORMIGA (2005) and are presented in Tables 10 and 11 (opposite page). This network has been used previously by some researchers (LEAL, 1995;LOPES, 2003;FORMIGA, 2005).…”

“…The input data for this problem are given in FORMIGA (2005) and are presented in Tables 10 and 11 (opposite page). This network has been used previously by some researchers (LEAL, 1995;LOPES, 2003;FORMIGA, 2005). The network data, in EPANET2 solver format, are available from http://www.lenhs.ct.ufpb.br/html/ benchmarks.html.…”

“…The network data, in EPANET2 solver format, are available from http://www.lenhs.ct.ufpb.br/html/ benchmarks.html. The optimum solution of $199.39 m. cost units is obtained if the pipes as listed in Table 13 are used resulting in a minimum pressure in the system at node 6 being 17.10 m. When the results obtained by Lenhsnet are compared with those obtained by Formiga (2005) ($202.80 m.), by using non-dominated sorting genetic algorithm -NSGA-II, it is concluded that the proposed model reduces the total cost value by 1.7%. …”

Βελτιστοποίηση Υπό Πίεση Ακτινωτών Αρδευτικών Δικτύων Με Χρήση Αλγόριθμου Αποικίας Μυρμηγκιών

“…Η μέθοδος εφαρμόστηκε στο HP (Σχήμα 3.2) και στο NYTP (Σχήμα 3.1), μόνο για την ελαχιστοποίηση του κόστους σωληνώσεων και στο δίκτυο Bessa Network (Gomes and Formiga, 2001) για το συνδυαστικό πρόβλημα κόστους σωληνώσεων και κόστους ενέργειας αντλιοστασίου. Επίσης, για το συνδυαστικό πρόβλημα εφαρμογή έγινε και σε ένα πραγματικό δίκτυο στη Βραζιλία, το R-9 (Formiga, 2005). Στο HP η λύση ήταν αρκετά μεγαλύτερη από τη γνωστή βέλτιστη, 6.42 εκ.…”