A Genetic Programming Approach to the Generation of Hyper-Heuristics for the Uncapacitated Examination Timetabling Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{conf/epia/PillayB07,

• author = "Nelishia Pillay and Wolfgang Banzhaf",
• title = "A Genetic Programming Approach to the Generation of Hyper-Heuristics for the Uncapacitated Examination Timetabling Problem",
• booktitle = "13th Portuguese Conference on Aritficial Intelligence, EPIA 2007",
• year = "2007",
• editor = "Jos{\'e} Neves and Manuel Filipe Santos and Jos{\'e} Machado",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• pages = "223--234",
• address = "Guimar{\~a}es, Portugal",
• month = dec # " 3-7",
• keywords = "genetic algorithms, genetic programming, hyper-heuristics, examination timetabling",
• isbn13 = "978-3-540-77000-8",
• URL = "http://www.cs.mun.ca/~banzhaf/papers/epia.pdf",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.2636",
• DOI = "doi:10.1007/978-3-540-77002-2_19",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• abstract = "Research in the field of examination timetabling has developed in two directions. The first looks at applying various methodologies to induce examination timetables. The second takes an indirect approach to the problem and examines the generation of heuristics or combinations of heuristics, i.e. hyper-heuristics, to be used in the construction of examination timetables. The study presented in this paper focuses on the latter area. This paper presents a first attempt at using genetic programming for the evolution of hyper-heuristics for the uncapacitated examination timetabling problem. The system has been tested on 9 benchmark examination timetabling problems. Clash-free timetables were found for all 9 nine problems. Furthermore, the performance of the genetic programming system is comparable to, and in a number of cases has produced better quality timetables, than other search algorithms used to evolve hyper-heuristics for this set of problems.{"}, bibsource = {"}OAI-PMH server at citeseerx.ist.psu.edu",
• notes = "Workshops: GAIW, AIASTS, ALEA, AMITA, BAOSW, BI, CMBSB, IROBOT, MASTA, STCS, and TEMA",

}

Genetic Programming entries for Nelishia Pillay Wolfgang Banzhaf

Citations