Development of a decision support system for the maintenance of water distribution network


BETTEMİR Ö. H. , Ozdemir O., FIRAT M.

PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, cilt.23, ss.1049-1054, 2017 (ESCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 23 Konu: 9
  • Basım Tarihi: 2017
  • Doi Numarası: 10.5505/pajes.2017.56823
  • Dergi Adı: PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI
  • Sayfa Sayıları: ss.1049-1054

Özet

Dealing with the failures of the water distribution network is an important decision making problem. If decision makers aim to immediately react all of the failures, then it is required to employ too many crews which will be idle throughout the low demand periods. On the other hand, if insufficient number of crews is employed, reaction will be too late and the adverse effects of the failure may be significant. Frequency of failures fluctuates seasonally which complicates the problem further. In this study, a decision support system which optimizes the maintenance of water distribution network problem by differential evolution algorithm is proposed. In this respect, past failure records of the Malatya Water Distribution System are used. Number of failures of the network is estimated for the future by using a regression model fed by the past records of failure. Future state of the network is modeled and number of failures is reckoned to estimate the reaction times to the failures. Optimum crew size which minimized the summation of the adverse effects of the failure and the employment cost is determined by Differential Evolution algorithm. Thus, number of crews which minimizes the maintenance cost of the prospected failures is determined. Implementation of the decision support system provides the opportunity of saving important amount of resource and money. Consequently, the local authorities which implement the proposed decision support system can reduce the maintenance cost and execute efficient employment policy.