Evolving Effective Bidding Functions for Auction based Resource Allocation Framework

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Mohamed Bahy Bader-El-Den and Shaheen Fatima",
  title =        "Evolving Effective Bidding Functions for Auction based
                 Resource Allocation Framework",
  year =         "2009",
  booktitle =    "International Conference on Evolutionary Computation
                 (ICEC 2009)",
  editor =       "Agostinho Rosa",
  address =      "Madeira, Portugal",
  month =        "5-7 " # oct,
  publisher =    "INSTICC Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-989-674-014-6",
  URL =          "https://www.researchgate.net/publication/221616501_Evolving_Effective_Bidding_Functions_for_Auction_based_Resource_Allocation_Framework",
  URL =          "https://researchportal.port.ac.uk/portal/en/publications/evolving-effective-bidding-functions-for-auction-based-resource-allocation-framework(5323b5d3-0e0a-446a-91d5-b64bb53a592f)/export.html",
  broken =       "http://eprints.port.ac.uk/id/eprint/3738",
  bibdate =      "2010-03-03",
  bibsource =    "DBLP,
  abstract =     "In this paper, we present an auction based resource
                 allocation framework. This framework, called GPAuc,
                 uses genetic programming for evolving bidding
                 functions. We describe GPAuc in the context of the exam
                 timetabling problem (ETTP). In the ETTP, there is a set
                 of exams, which must be assigned to a predefined set of
                 slots. Here, the exam time tabling system is the seller
                 that auctions a set of slots. 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 need to find the bidders' optimal bids.
                 This is done using genetic programming. The
                 effectiveness of GPAuc is demonstrated experimentally
                 by comparing it with some existing benchmarks for exam
  notes =        "IJCCI

                 Appears not to be in the book, Computational
                 Intelligence ISBN:978-3-642-20205-6, published by

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