Genetic programming for auction based scheduling

Mohamed Bader, S. Fatima

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


In this paper, we present a genetic programming (GP) framework for evolving agent's binding function (GPAuc) in a resource allocation problem. The framework is tested on the exam timetabling problem (ETP). There is a set of exams, which have to be assigned to a predefined set of slots and rooms. 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 timetabling.
Original languageEnglish
Title of host publicationGenetic programming: 13th European conference, EuroGP 2010, Istanbul, Turkey, April 7-9 2010, proceedings
EditorsA. Esparcia-Alcazar, A. Ekart, S. Silva, S. Dignum, A. Uyar
Place of PublicationBerlin
Number of pages12
ISBN (Print)9783642121487
Publication statusPublished - Apr 2010
EventProceedings of the 13th European Conference on Genetic Programming - Istanbul, Turkey
Duration: 7 Apr 20109 Apr 2010

Publication series

NameLecture notes in computer science


ConferenceProceedings of the 13th European Conference on Genetic Programming
Abbreviated titleEuroGP 2010


  • Scheduling
  • Auction
  • Genetic Programming
  • Multiagent System


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