Co-evolutionary hyper-heuristic method for auction based scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Shaheen Fatima and Mohamed Bader-El-Den",
  title =        "Co-evolutionary hyper-heuristic method for auction
                 based scheduling",
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "In this paper, we present a co-evolutionary
                 hyper-heuristic method for solving a sequential auction
                 based resource allocation problem. The method combines
                 genetic programming (GP) for evolving agent's bidding
                 functions for the individual auctions with genetic
                 algorithms (GAs) for evolving an optimal ordering for
                 auctions. The framework is evaluated in the context of
                 the exam timetabling problem (ETTP). In this problem,
                 there is a set of exams, which have to be assigned to a
                 predefined set of slots. Here, the exam time tabling
                 system is the seller that sells a set of slots in a
                 series of auctions. There is one auction for each slot.
                 The exams are viewed as the bidding agents in need of
                 slots. The problem is then to find a schedule (i.e., a
                 slot for each exam) such that the total cost of
                 conducting the exams as per the schedule is minimised.
                 In order to arrive at such a schedule, we find the
                 bidders optimal bids for an auction using GP. We
                 combine this with a GA that finds an optimal ordering
                 for conducting the auctions. The effectiveness of this
                 co-evolutionary method is demonstrated experimentally
                 by comparing it with some existing benchmarks for exam
  DOI =          "doi:10.1109/CEC.2010.5586319",
  notes =        "WCCI 2010. Also known as \cite{5586319}",

Genetic Programming entries for Shaheen Fatima Mohamed Bahy Bader-El-Den