Evolving effective bidding functions for auction based resource allocation framework

Mohamed Bader, S. Fatima

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


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 time-tabling.
Original languageEnglish
Title of host publicationInternational conference on evolutionary computation, (ICEC 2009)
EditorsA. Rosa
Place of PublicationMadeira, Portugal
Number of pages4
ISBN (Print)9789896740146
Publication statusPublished - Oct 2009
EventInternational Conference on Evolutionary Computation -
Duration: 1 Oct 2009 → …


ConferenceInternational Conference on Evolutionary Computation
Abbreviated titleICEC 2009
Period1/10/09 → …


  • Genetic Programming
  • Auctions


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