Practice and Theory of Automated Timetabling V

1. Front Matter

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2. General Issues

   1. Front Matter

      Pages 1-1

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   2. Learning User Preferences in Distributed Calendar Scheduling

      • Jean Oh, Stephen F. Smith

      Pages 3-16

   3. Semantic Components for Timetabling

      • Nele Custers, Patrick De Causmaecker, Peter Demeester, Greet Vanden Berghe

      Pages 17-33

   4. An Open Interactive Timetabling Tool

      • Sylvain Piechowiak, Jingxua Ma, René Mandiau

      Pages 34-50

   5. Distributed Choice Function Hyper-heuristics for Timetabling and Scheduling

      • Prapa Rattadilok, Andy Gaw, Raymond S. K. Kwan

      Pages 51-67

3. Transport Timetabling

   1. Front Matter

      Pages 69-69

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   2. A Hybridised Integer Programming and Local Search Method for Robust Train Driver Schedules Planning

      • Ignacio Laplagne, Raymond S. K. Kwan, Ann S. K. Kwan

      Pages 71-85

   3. Logistics Service Network Design for Time-Critical Delivery

      • Cynthia Barnhart, Su Shen

      Pages 86-105

4. University Course Timetabling

   1. Front Matter

      Pages 107-107

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   2. The University Course Timetabling Problem with a Three-Phase Approach

      • Philipp Kostuch

      Pages 109-125

   3. Minimal Perturbation Problem in Course Timetabling

      • Tomáš Müller, Hana Rudová, Roman Barták

      Pages 126-146

   4. Feature Selection in a Fuzzy Student Sectioning Algorithm

      • Mahmood Amintoosi, Javad Haddadnia

      Pages 147-160

   5. A Column Generation Scheme for Faculty Timetabling

      • Andrea Qualizza, Paolo Serafini

      Pages 161-173

5. School Timetabling

   1. Front Matter

      Pages 175-175

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   2. Decomposition and Parallelization of Multi-resource Timetabling Problems

      • Petr Šlechta

      Pages 177-189

   3. Interactively Solving School Timetabling Problems Using Extensions of Constraint Programming

      • Hadrien Cambazard, Fabien Demazeau, Narendra Jussien, Philippe David

      Pages 190-207

   4. A Tiling Algorithm for High School Timetabling

      • Jeffrey H. Kingston

      Pages 208-225

6. Project Scheduling

   1. Front Matter

      Pages 227-227

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   2. Lower Bounds for the Multi-skill Project Scheduling Problem with Hierarchical Levels of Skills

      • Odile Bellenguez, Emmanuel Néron

      Pages 229-243

Thisvolumecontainsaselectionofpapersfromthe5thInternationalConference on the Practice and Theory of Automated Timetabling (PATAT 2004) held in Pittsburgh, USA, August 18–20, 2004. Indeed, as we write this preface, in the Summer of 2005, we note that we are about one month away from the tenth anniversary of the very ?rst PATAT conference in Edinburgh. Since those very early days, the conference series has gone from strength to strength and this volume represents the latest in a series of ?ve rigorously refereed volumes which showcase a broad spectrum of ground-breaking timetabling research across a very wide range of timetabling problems and applications. Timetabling is an area that unites a number of disparate ?elds and which cuts across a number of diverse academic disciplines. While the most obvious instances of timetabling occur in educational institutions, timetabling also - pears in sports applications, transportation planning, project scheduling, and many other ?elds. Viewing timetabling as a unifying theme enables researchers fromthesevariousareastolearnfromeachotherandtoextendtheirown- searchandpracticeinnewandinnovativeways.Thisvolumecontinuesthetrend of the conference series to extend the de?nition of timetabling beyond its edu- tional roots. In this volume, seven of the 19 papers involve domains other than education. Of course, educationaltimetabling remains at the coreof timetabling research, and the papers in this volume represent the full range of this area including exam timetabling, room scheduling, and class rostering.

• algorithms
• automated timetabling
• class-teacher timetabling
• combinatorial optimization
• constraint programming
• distributed timetabling
• evolutionary algorithm
• evolutionary algorithms
• fuzzy approaches
• genetic algorithms
• heuristic methodologies
• heuristics
• integer programming
• learning
• programming
• algorithm analysis and problem complexity

• Automated Scheduling, Optimisation and Planning Group, School of Computer Science & IT, University of Nottingham, Nottingham, UK

  Edmund Burke

• Tepper School of Business, Carnegie Mellon University, Pittsburgh, USA

  Michael Trick

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