Integer and combinatorial optimization
Integer and combinatorial optimization
Formulating a mixed integer programming problem to improve solvability
Operations Research
Record breaking optimization results using the ruin and recreate principle
Journal of Computational Physics
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization
Journal of Heuristics
A Survey of Automated Timetabling
Artificial Intelligence Review
Computer-Aided School and University Timetabling: The New Wave
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Recent Developments in Practical Course Timetabling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Progress in Linear Programming-Based Algorithms for Integer Programming: An Exposition
INFORMS Journal on Computing
A survey of very large-scale neighborhood search techniques
Discrete Applied Mathematics
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Exploring relaxation induced neighborhoods to improve MIP solutions
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
A Computational Study of a Cutting Plane Algorithm for University Course Timetabling
Journal of Scheduling
Decomposition and Dynamic Cut Generation in Integer Linear Programming
Mathematical Programming: Series A and B
Equitable colorings of bounded treewidth graphs
Theoretical Computer Science - Graph colorings
Vehicle routing problem with elementary shortest path based column generation
Computers and Operations Research
A general heuristic for vehicle routing problems
Computers and Operations Research
A computational study of local search algorithms for Italian high-school timetabling
Journal of Heuristics
A perspective on bridging the gap between theory and practice in university timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Very large-scale neighborhood search techniques in timetabling problems
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Modeling and solution of a complex university course timetabling problem
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Optimal university course timetables and the partial transversal polytope
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
A unified view on hybrid metaheuristics
HM'06 Proceedings of the Third international conference on Hybrid Metaheuristics
Formulations and reformulations in integer programming
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A taxonomy of cooperative search algorithms
HM'05 Proceedings of the Second international conference on Hybrid Metaheuristics
A column generation scheme for faculty timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
Computers and Operations Research
Solving effectively the school timetabling problem using particle swarm optimization
Expert Systems with Applications: An International Journal
A hybrid metaheuristic approach to the university course timetabling problem
Journal of Heuristics
Generalising algorithm performance in instance space: a timetabling case study
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Solution approaches to the course timetabling problem
Artificial Intelligence Review
A Two-Stage Decomposition of High School Timetabling applied to cases in Denmark
Computers and Operations Research
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In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition (ITC), also known as the Udine Course Timetabling problem. The goal is to find an assignment of events to periods and rooms, so that the assignment of events to periods is a feasible bounded colouring of an associated conflict graph and the linear combination of the numbers of violations of four soft constraints is minimised. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.