Genetic Programming for Auction Based Scheduling

  • Mohamed Bader-El-Den
  • Shaheen Fatima
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6021)


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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mohamed Bader-El-Den
    • 1
  • Shaheen Fatima
    • 1
  1. 1.Department of Computer ScienceLoughborough UniversityLoughboroughUK

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