Identifying contaminant sources for water distribution systems using a hybrid method

References

• van Bloemen Waanders , B. G. Nonlinear programming strategies for source detection of municipal water networks . Proceedings of the ASCE world water and environmental congress . June 23–26 , Philadelphia , PA . Weston , VA : ASCE .
   Google Scholar
• Brumbelow , K. Virtual cities for water distribution and infrastructure system research . Proceedings of world environmental and water resources congress . May 15–19 , Tampa , Florida. Weston , VA : ASCE .
   Google Scholar
• Clark , R. M. and Deininger , R. A. 2000 . Protecting the Nation's critical infrastructure: the vulnerability of U.S. water supply systems . Journal of Contingencies and Crisis Management , 8 ( 2 ) : 73 – 80 .
   Google Scholar
• De Sanctis , A. E. , Shang , F. and Uber , J. G. Determining possible contaminant sources through flow path analysis . August 27–30 , Cincinnatti , OH . Proceedings of water distribution systems analysis symposium , Weston , VA : ASCE .
   Google Scholar
• Di Cristo , C. and Leopardi , A. 2008 . Pollution source identification of accidental contamination in water distribution networks . Journal of Water Resources Planning and Management , 134 ( 2 ) : 197 – 202 .
   Web of Science ®Google Scholar
• Espinoza , F. P. , Minsker , B. S. and Goldberg , D. E. 2005 . Adaptive hybrid genetic algorithm for groundwater remediation design . Journal of Water Resources Planning and Management , 131 ( 1 ) : 14 – 24 .
   Web of Science ®Google Scholar
• Gen , M. and Chen , R. W. 1997 . Genetic algorithms and engineering design , New York : John Wiley & Sons .
   Google Scholar
• Guan , J. 2006 . Identification of contaminant sources in water distribution systems using simulation–optimization method: case study . Journal of Water Resources Planning and Management , 132 ( 4 ) : 252 – 262 .
   Web of Science ®Google Scholar
• Hart , W. E. 1994 . Adaptive global optimization with local search , University of California, San Diego . Thesis (PhD)
   Google Scholar
• Holland , J. H. 1975 . Adaptation in natural and artificial systems , Ann Arbor , MI : University of Michigan Press .
   Google Scholar
• Hooke , R. and Jeeves , T. A. 1961 . Direct search’ solution of numerical and statistical problems . Journal of the Association for Computing Machinery (ACM) , 8 ( 2 ) : 212 – 229 .
   Google Scholar
• Laird , C. L. 2005 . Contamination source determination for water networks . Journal of Water Resources Planning and Management , 131 ( 2 ) : 125 – 134 .
   Web of Science ®Google Scholar
• Laird , C. D. , Biegler , L. T. and van Bloemen Waanders , B. G. 2006 . Mixed-integer approach for obtaining unique solutions in source inversion of water networks . Journal of Water Resources Planning and Management , 132 ( 4 ) : 242 – 251 .
   Web of Science ®Google Scholar
• Land , M. W.S. 1998 . Evolutionary algorithms with local search for combinatorial optimization , University of California, San Diego . Thesis (PhD)
   Google Scholar
• Liu , L. , Ranjithan , S. and Mahinthakumar , G. 2011a . Contamination source identification in water distribution systems using an adaptive dynamic optimization procedure . Journal of Water Resources Planning and Management , 137 ( 2 ) : 183 – 192 .
   Web of Science ®Google Scholar
• Liu , L. , Sankarasubramanian , A. and Ranjithan , S. 2011b . Logistic regression analysis to estimate contaminant sources in water distribution systems . Journal of Hydroinformatics , 13 ( 3 ) : 545 – 557 .
   Web of Science ®Google Scholar
• Mahinthakumar , G. K. and Sayeed , M. 2005 . Hybrid genetic algorithm – local search methods for solving groundwater source identification inverse problems . Journal of Water Resources Planning and Management , 131 ( 1 ) : 45 – 57 .
   Web of Science ®Google Scholar
• Nelder , J. A. and Mead , R. 1965 . A simplex method for function minimization . Computer Journal , 7 ( 4 ) : 308 – 313 .
   Web of Science ®Google Scholar
• Partheepan , R. 2003 . Hybrid genetic algorithms , Raleigh , NC : North Carolina State University . Thesis (MSc)
   Google Scholar
• Preis , A. and Ostfeld , A. 2007 . A contamination source identification model for water distribution system security . Engineering Optimization , 39 ( 8 ) : 941 – 951 .
   Web of Science ®Google Scholar
• Preis , A. and Ostfeld , A. 2008 . Genetic algorithm for contaminant source characterization using imperfect sensors . Civil Engineering and Environmental Systems , 25 ( 1 ) : 29 – 39 .
   Web of Science ®Google Scholar
• Rossman , L. A. 2000 . EPANET user's manual , Cincinnati , OH : Risk Reduction Engineering Laboratory, U.S. Environmental Protection Agency .
   Google Scholar
• Xu , Y. G. , Li , G. R. and Wu , Z. P. 2001 . A novel hybrid genetic algorithm using local optimizer based on heuristic pattern move . Applied Artificial Intelligence , 15 ( 7 ) : 601 – 631 .
   Web of Science ®Google Scholar
• Yeh , H. D. , Chang , T. H. and Lin , Y. C. 2007 . Groundwater contaminant source identification by a hybrid heuristic approach . Water Resources Research , 43 ( 9 ) : W09420
   Web of Science ®Google Scholar
• Zechman , E. M. and Ranjithan , S. 2009 . Evolutionary computation-based methods for characterising contaminant sources in a water distribution system . Journal of Water Resources Planning and Management , 135 ( 5 ) : 334 – 343 .
   Web of Science ®Google Scholar