scip_solution_read


scip_solution_read, a MATLAB code which reads a file created by the integer programming package SCIP, representing the solution of a polyomino tiling problem, and writes out a simple ASCII file that can be read by load().

For our problems, SCIP reads an LP file defining an integer linear system, whose solution is constrained to be binary, that is, each entry is either 0 or 1. The solution file returned by SCIP only reports the nonzero values.

This program makes some strong assumptions on the contents of the SCIP solution file:

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

scip_solution_read is available in a MATLAB version.

Related Programs and Data:

scip_solution_read_test

cplex_solution_read, a MATLAB code which extracts solution data from a CPLEX result file; CPLEX can be "fed" by an LP file created by polyomino_monohedral_matrix() or polyomino_multihedral_matrix(), and the results can be displayed by polyomino_monohedral_tiling_print() or polyomino_multihedral_tiling_print().

gurobi_solution_read, a MATLAB code which reads a file created by the optimization package GUROBI, representing the solution of a polyomino tiling problem, and writes out a simple ASCII file that can be read by load().

polyominoes, a MATLAB code which defines, solves, and plots a variety of polyomino tiling problems, which are solved by a direct algebraic approach involving the reduced row echelon form (RREF) of a specific matrix, instead of the more typical brute-force or backtracking methods.

Reference:

  1. https://scip.zib.de/ , the SCIP home page.
  2. The SCIP Optimization Suite 5.0,
    Ambros Gleixner, Leon Eifler, Tristan Gally, Gerald Gamrath, Patrick Gemander, Robert Lion Gottwald, Gregor Hendel, Christopher Hojny, Thorsten Koch, Matthias Miltenberger, Benjamin Müller, Marc E. Pfetsch, Christian Puchert, Daniel Rehfeldt, Franziska Schlösser, Felipe Serrano, Yuji Shinano, Jan Merlin Viernickel, Stefan Vigerske, Dieter Weninger, Jonas T. Witt, Jakob Witzig,
    ZIB-Report 17-61, Zuse Institute Berlin, December 2017.

Source Code:


Last revised on 11 March 2019.