Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Spot: Scheduling Programs Optimally for Television
Management Science
Approximation algorithms for maximization problems arising in graph partitioning
Journal of Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A 0.5-Approximation Algorithm for MAX DICUT with Given Sizes of Parts
SIAM Journal on Discrete Mathematics
Approximation algorithms for MAX-3-CUT and other problems via complex semidefinite programming
Journal of Computer and System Sciences - STOC 2001
Approximate Local Search in Combinatorial Optimization
SIAM Journal on Computing
Scheduling Commercials on Broadcast Television
Operations Research
An approximation algorithm for max p-section
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
The capacitated max-k-cut problem
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Hi-index | 0.00 |
We extend a previous model for scheduling commercial advertisements during breaks in television programming. The proposed extension allows differential weighting of conflicts between pairs of commercials. We formulate the problem as a capacitated generalization of the max k-cut problem in which the vertices of a graph correspond to commercial insertions and the edge weights to the conflicts between pairs of insertions. The objective is to partition the vertices into k capacitated sets to maximize the sum of conflict weights across partitions. We note that the problem is NP-hard. We extend a previous local-search procedure to allow for the differential weighting of edge weights. We show that for problems with equal insertion lengths and break durations, the worst-case bound on the performance of the proposed algorithm increases with the number of program breaks and the number of insertions per break, and that it is independent of the number of conflicts between pairs of insertions. Simulation results suggest that the algorithm performs well even if the problem size is small.