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Authors: Mohamed Bader-El-Den and Shaheen Fatima

Affiliation: Loughborough University, United Kingdom

Keyword(s): Genetic programming, Multi-agent systems, Resource allocation, Timetabling, Auctions based systems, Heuristics.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Evolutionary Computing ; Game Theory Applications ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

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 time-tabling.

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Paper citation in several formats:
Bader-El-Den, M. and Fatima, S. (2009). EVOLVING EFFECTIVE BIDDING FUNCTIONS FOR AUCTION BASED RESOURCE ALLOCATION FRAMEWORK. In Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC; ISBN 978-989-674-014-6; ISSN 2184-3236, SciTePress, pages 310-313. DOI: 10.5220/0002324203100313

@conference{icec09,
author={Mohamed Bader{-}El{-}Den. and Shaheen Fatima.},
title={EVOLVING EFFECTIVE BIDDING FUNCTIONS FOR AUCTION BASED RESOURCE ALLOCATION FRAMEWORK},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC},
year={2009},
pages={310-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002324203100313},
isbn={978-989-674-014-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC
TI - EVOLVING EFFECTIVE BIDDING FUNCTIONS FOR AUCTION BASED RESOURCE ALLOCATION FRAMEWORK
SN - 978-989-674-014-6
IS - 2184-3236
AU - Bader-El-Den, M.
AU - Fatima, S.
PY - 2009
SP - 310
EP - 313
DO - 10.5220/0002324203100313
PB - SciTePress