HEURISTIC BASED OPTIMAL DESIGN OF WATER DISTRIBUTION NETWORKS

  • Danee Joycee.C.S SathyabamaUniversity, Chennai, India
  • Dr.K. Srinivasan Indian Institute of Technology, Chennai ,India
  • Dr.M. Helen Santhi VIT University, Chennai, India

Abstract

Water supply systems form an integral part of modern civilization. A modern water supply may include facilities for collection and storage, transportation, pumping, treatment and distribution; the design of a network for the above becomes a complex engineering task because it adopts traditional method to find solution, which is basically a trial-and-error based one and hence is not efficient. In order to overcome these inefficiencies, methods such as Optimization or Search Algorithms is suggested. The present study aims at comparing the performance of heuristic based design of Water Distribution Networks with Genetic Algorithm (GA) optimization. Since, a heuristic method alone cannot guarantee optimal solutions, it has been combined with GA to improve its performance. In fact the results obtained from this heuristic method are serving as the initial population for NSGA-II and hence these should not be directly compared with the optimal solution obtained from NSGA-II. For the first method, a multi-objective evolutionary algorithm, “Fast Elitist NonDominated Sorting Genetic Algorithm-II (NSGA-II)” of Deb et al. (2000) is used; while for the second, heuristic method, Critical Path Concept (Bhave, 1977) in combination with NSGA-II is used. Critical Path Concept above said significantly reduces the running time taken by computer for searching various combinations before arriving at the optimal solution.These two methods have been tested on several networks, including networks used for benchmark testing namely, two loop and three loop (Hanoi) networks.

Published
2013-08-01
How to Cite
JOYCEE.C.S, Danee; SRINIVASAN, Dr.K.; HELEN SANTHI, Dr.M.. HEURISTIC BASED OPTIMAL DESIGN OF WATER DISTRIBUTION NETWORKS. EACEF - International Conference of Civil Engineering, [S.l.], v. 1, n. 1, p. 069, aug. 2013. Available at: <http://proceeding.eacef.com/ojs/index.php/EACEF/article/view/302>. Date accessed: 12 aug. 2020.