Genetic Programming for Auction Based Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.8620

@InProceedings{Bader-El-Den:2010:EuroGP,

• author = "Mohamed Bader-El-Den and Shaheen Fatima",
• title = "Genetic Programming for Auction Based Scheduling",
• booktitle = "Proceedings of the 13th European Conference on Genetic Programming, EuroGP 2010",
• year = "2010",
• editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and Sara Silva and Stephen Dignum and A. Sima Uyar",
• volume = "6021",
• series = "LNCS",
• pages = "256--267",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-12147-0",
• DOI = "10.1007/978-3-642-12148-7_22",
• abstract = "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.",
• notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010 held in conjunction with EvoCOP2010 EvoBIO2010 and EvoApplications2010",

}

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

Citations