A Genetic Programming Approach for Solving the Linear Ordering Problem

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  author =       "Petrica C. Pop and Oliviu Matei",
  title =        "A Genetic Programming Approach for Solving the Linear
                 Ordering Problem",
  booktitle =    "Proceedings of the 7th International Conference on
                 Hybrid Artificial Intelligent Systems (HAIS 2012) Part
  year =         "2012",
  editor =       "Emilio Corchado and Vaclav Snasel and 
                 Ajith Abraham and Michal Wozniak and Manuel Grana and Sung-Bae Cho",
  volume =       "7209",
  pages =        "331--338",
  series =       "Lecture Notes in Computer Science",
  address =      "Salamanca, Spain",
  month =        mar # " 28-30",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, linear
                 ordering problem, heuristics, evolutionary
  isbn13 =       "978-3-642-28930-9",
  DOI =          "doi:10.1007/978-3-642-28931-6_32",
  size =         "8 pages",
  abstract =     "The linear ordering problem (LOP) consists in
                 rearranging the rows and columns of a given square
                 matrix such that the sum of the super-diagonal entries
                 is as large as possible. The LOP has a significant
                 number of important practical applications. In this
                 paper we describe an efficient genetic programming
                 based algorithm, designed to find high quality
                 solutions for LOP. The computational results obtained
                 for two sets of benchmark instances indicate that our
                 proposed heuristic is competitive to previous methods
                 for solving the LOP.",
  affiliation =  "Dept. of Mathematics and Informatics, North University
                 of Baia Mare, Romania",
  bibdate =      "2012-03-19",
  bibsource =    "DBLP,

Genetic Programming entries for Petrica C Pop Oliviu Matei