Hypervolume-Driven Analytical Programming for Solar-Powered Irrigation System Optimization

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "T. Ganesan and I. Elamvazuthi and 
                 Ku Zilati Ku Shaari and P. Vasant",
  title =        "Hypervolume-Driven Analytical Programming for
                 Solar-Powered Irrigation System Optimization",
  booktitle =    "Nostradamus 2013: Prediction, Modeling and Analysis of
                 Complex Systems",
  year =         "2013",
  editor =       "Ivan Zelinka and Guanrong Chen and 
                 Otto E. R{\"o}ssler and Vaclav Snasel and Ajith Abraham",
  volume =       "210",
  series =       "Advances in Intelligent Systems and Computing",
  pages =        "147--154",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Analytical
  isbn13 =       "978-3-319-00542-3",
  DOI =          "doi:10.1007/978-3-319-00542-3_15",
  abstract =     "In the field of alternative energy and sustainability,
                 optimization type problems are regularly encountered.
                 In this paper, the Hypervolume-driven Analytical
                 Programming (Hyp-AP) approaches were developed. This
                 method was then applied to the multi-objective (MO)
                 design optimization of a real-world photovoltaic
                 (PV)-based solar powered irrigation system. This
                 problem was multivariate, nonlinear and multiobjective.
                 The Hyp-AP method was used to construct the approximate
                 Pareto frontier as well as to identify the best
                 solution option. Some comparative analysis was
                 performed on the proposed method and the approach used
                 in previous work.",

Genetic Programming entries for Timothy Ganesan I Elamvazuthi Ku Zilati Ku Shaari Pandian Vasant