Cyclic transfers in school timetabling

In this paper we propose a neighbourhood structure based on sequential/cyclic moves and a cyclic transfer algorithm for the high school timetabling problem. This method enables execution of complex moves for improving an existing solution, while dealing with the challenge of exploring the neighbourhood efficiently. An improvement graph is used in which certain negative cycles correspond to the neighbours; these cycles are explored using a recursive method. We address the problem of applying large neighbourhood structure methods on problems where the cost function is not exactly the sum of independent cost functions, as it is in the set partitioning problem. For computational experiments we use four real world data sets for high school timetabling in the Netherlands and England. We present results of the cyclic transfer algorithm with different settings on these data sets. The costs decrease by 8–28% if we use the cyclic transfers for local optimization compared to our initial solutions. The quality of the best initial solutions are comparable to the solutions found in practice by timetablers.

[1]  Dushyant Sharma,et al.  Multi-exchange neighborhood structures for the capacitated minimum spanning tree problem , 2001, Math. Program..

[2]  Gerhard F. Post,et al.  A Case Study for Timetabling in a Dutch Secondary School , 2006, PATAT.

[3]  Dushyant Sharma,et al.  Very Large-Scale Neighborhood Search for the Quadratic Assignment Problem , 2007, INFORMS J. Comput..

[4]  Jeffrey H. Kingston,et al.  An XML format for benchmarks in High School Timetabling , 2010, Ann. Oper. Res..

[5]  R. Alvarez-Valdes,et al.  Constructing Good Solutions for the Spanish School Timetabling Problem , 1996 .

[6]  Moshe Dror,et al.  A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem , 2007, J. Oper. Res. Soc..

[7]  Andreas Drexl,et al.  Distribution requirements and compactness constraints in school timetabling , 1997 .

[8]  Andrea Schaerf,et al.  Local search techniques for large high school timetabling problems , 1999, IEEE Trans. Syst. Man Cybern. Part A.

[9]  Edmund K. Burke,et al.  The practice and theory of automated timetabling , 2014, Annals of Operations Research.

[10]  M. Yagiura,et al.  Recent metaheuristic algorithms for the generalized assignment problem , 2004, International Conference on Informatics Research for Development of Knowledge Society Infrastructure, 2004. ICKS 2004..

[11]  Efthymios Housos,et al.  Timetabling for Greek high schools , 1997 .

[12]  Nelson Maculan,et al.  Strong bounds with cut and column generation for class-teacher timetabling , 2012, Ann. Oper. Res..

[13]  Peter I. Cowling,et al.  COMBINING HUMAN AND MACHINE INTELLIGENCE TO PRODUCE EFFECTIVE EXAMINATION TIMETABLES , 2002 .

[14]  J. Orlin,et al.  Solving Parallel Machine Scheduling Problems with Variable Depth Local Search , 2004 .

[15]  Efthymios Housos,et al.  School timetabling for quality student and teacher schedules , 2009, J. Sched..

[16]  Jeffrey H. Kingston Modelling Timetabling Problems with STTL , 2000, PATAT.

[17]  Mike Wright,et al.  School Timetabling Using Heuristic Search , 1996 .

[18]  James B. Orlin,et al.  Very Large-Scale Neighborhood Search Techniques in Timetabling Problems , 2006, PATAT.

[19]  Edmund K. Burke,et al.  Practice and Theory of Automated Timetabling II , 1997, Lecture Notes in Computer Science.

[20]  Abraham P. Punnen,et al.  A survey of very large-scale neighborhood search techniques , 2002, Discret. Appl. Math..

[21]  Krishna C. Jha VERY LARGE-SCALE NEIGHBORHOOD SEARCH HEURISTICS FOR COMBINATORIAL OPTIMIZATION PROBLEMS , 2004 .

[22]  Onno B. de Gans,et al.  A computer timetabling system for secondary schools in the Netherlands , 1981 .

[23]  Kate A. Smith,et al.  Hopfield neural networks for timetabling: formulations, methods, and comparative results , 2003 .

[24]  Dominique de Werra On a Multiconstrained Model for Chromatic Scheduling , 1999, Discret. Appl. Math..

[25]  D. de Werra,et al.  An introduction to timetabling , 1985 .

[26]  Abraham P. Punnen,et al.  Domination analysis of some heuristics for the traveling salesman problem , 2002, Discret. Appl. Math..

[27]  Marco Dorigo,et al.  Metaheuristics for High School Timetabling , 1998, Comput. Optim. Appl..

[28]  Marcone J. F. Souza,et al.  An Efficient Tabu Search Heuristic for the School Timetabling Problem , 2004, WEA.

[29]  Andrea Schaerf,et al.  A Survey of Automated Timetabling , 1999, Artificial Intelligence Review.

[30]  A. Hertz Tabu search for large scale timetabling problems , 1991 .

[31]  RJ Roy Willemen,et al.  School timetable construction : algorithms and complexity , 2002 .

[32]  Fred W. Glover,et al.  A very large-scale neighborhood search algorithm for the multi-resource generalized assignment problem , 2004, Discret. Optim..

[33]  Sanja Petrovic,et al.  Recent research directions in automated timetabling , 2002, Eur. J. Oper. Res..

[34]  James B. Orlin,et al.  Theory of cyclic transfers , 1989 .

[35]  Jeffrey H. Kingston,et al.  The Solution of Real Instances of the Timetabling Problem , 1993, Comput. J..

[36]  Peter I. Cowling,et al.  Opening the Information Bottleneck in Complex Scheduling Problems with a Novel Representation: STARK Diagrams , 2002, Diagrams.

[37]  David Abramson,et al.  Constructing school timetables using simulated annealing: sequential and parallel algorithms , 1991 .

[38]  Gilbert Laporte,et al.  Recent Developments in Practical Course Timetabling , 1997, PATAT.

[39]  Norman L. Lawrie An integer linear programming model of a school timetabling problem , 1969, Comput. J..

[40]  Efthymios Housos,et al.  Constraint programming approach for school timetabling , 2003, Comput. Oper. Res..

[41]  James B. Orlin,et al.  New neighborhood search algorithms based on exponentially large neighborhoods , 2001 .

[42]  Peter I. Cowling,et al.  Integrating human abilities with the power of automated scheduling systems: representational epistemological interface design , 2003 .

[43]  Peter I. Cowling,et al.  Integrating human abilities and automated systems for timetabling: a competition using STARK and HuSSH representations at the PATAT 2002 conference , 2002 .

[44]  Brian W. Kernighan,et al.  An Effective Heuristic Algorithm for the Traveling-Salesman Problem , 1973, Oper. Res..

[45]  Paul M. Thompson,et al.  Cyclic Transfer Algorithm for Multivehicle Routing and Scheduling Problems , 1993, Oper. Res..

[46]  Moshe Dror,et al.  Investigating Ahuja–Orlin’s large neighbourhood search approach for examination timetabling , 2007, OR Spectr..

[47]  Gerhard J. Woeginger,et al.  A study of exponential neighborhoods for the Travelling Salesman Problem and for the Quadratic Assignment Problem , 2000, Math. Program..

[48]  Natashia Boland,et al.  Accelerated label setting algorithms for the elementary resource constrained shortest path problem , 2006, Oper. Res. Lett..

[49]  Edmund Ph. D. Burke,et al.  Practice and theory of automated timetabling II : second International Conference, PATAT '97, Toronto, Canada, August 20-22, 1997 : selected papers , 1998 .

[50]  Jeffrey H. Kingston A Tiling Algorithm for High School Timetabling , 2004, PATAT.

[51]  Luiz Antonio Nogueira Lorena,et al.  A Constructive Evolutionary Approach to School Timetabling , 2001, EvoWorkshops.