Lagrangean decomposition: A model yielding stronger lagrangean bounds
Mathematical Programming: Series A and B
Integer and combinatorial optimization
Integer and combinatorial optimization
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Generating convex polyominoes at random
FPSAC '93 Proceedings of the 5th conference on Formal power series and algebraic combinatorics
Reconstructing convex polyominoes from horizontal and vertical projections
Theoretical Computer Science
On the precise number of (0,1)-matrices in U(R,S)
Discrete Mathematics
The reconstruction of polyominoes from their orthogonal projections
Information Processing Letters
Generation and empirical investigation of hv-convex discrete sets
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Approximating hv-convex binary matrices and images from discrete projections
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
On the number of hv-convex discrete sets
IWCIA'08 Proceedings of the 12th international conference on Combinatorial image analysis
Hi-index | 0.00 |
We consider a variant of the NP-hard problem of reconstructing hv-convex (0,1)-matrices from known row and column sums. Instead of requiring the ones to occur consecutively in each row and column, we maximize the number of neighboring ones. This is reformulated as an integer programming problem. A solution method based on variable splitting is proposed and tested with good results on moderately sized test problems.