Minimization of the number of breaks in sports scheduling problems using constraint programming
DIMACS workshop on on Constraint programming and large scale discrete optimization
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Improved Rounding Techniques for the MAX 2-SAT and MAX DI-CUT Problems
Proceedings of the 9th International IPCO Conference on Integer Programming and Combinatorial Optimization
Scheduling a Major College Basketball Conference
Operations Research
Approximating the value of two power proof systems, with applications to MAX 2SAT and MAX DICUT
ISTCS '95 Proceedings of the 3rd Israel Symposium on the Theory of Computing Systems (ISTCS'95)
Minimizing breaks by maximizing cuts
Operations Research Letters
A polynomial-time algorithm to find an equitable home-away assignment
Operations Research Letters
On the application of graph colouring techniques in round-robin sports scheduling
Computers and Operations Research
On the separation in 2-period double round robin tournaments with minimum breaks
Computers and Operations Research
Semidefinite programming based approaches to home-away assignment problems in sports scheduling
AAIM'05 Proceedings of the First international conference on Algorithmic Applications in Management
The timetable constrained distance minimization problem
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
A polynomial-time algorithm to find an equitable home-away assignment
Operations Research Letters
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This paper considers the break minimization problem in sports timetabling. The problem is to find, under a given timetable of a round-robin tournament, a home-away assignment that minimizes the number of breaks, i.e., the number of occurrences of consecutive matches held either both at away or both at home for a team. We formulate the break minimization problem as MAX RES CUT and MAX 2SAT, and apply Goemans and Williamson's approximation algorithm using semidefinite programming. Computational experiments show that our approach quickly generates solutions of good approximation ratios.