The 0-1 Knapsack problem, which is, for a thief, to pick those items that have as much total value as possible while not exceeding the knapsack’s weight limit, using dynamic programming. In this ...

The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on ...

Learn how to evaluate various linear programming methods and algorithms in Matlab using tips and tricks for performance, accuracy, and robustness.

10. Appendix: some linear program solvers and MATLAB codes 10.1 Some linear program solvers There are many solvers available for linear optimization. Most of these codes offer linear programming ...

Learn how to use MATLAB for data analysis, machine learning, and scientific computing. Discover the functions and features of MATLAB for statistical programming.

In this paper, we compare and discuss benchmarks of common linear algebra matrix computations using Matlab and scientific python (SciPy). The benchmarks presented here are from the user-standpoint ...

Zhang, Y. (1996) Solving Large-Scale Linear Programs by Interior-Point Methods under the Matlab Environment, Tech. rep., Department of Mathematics and Statistics, University of Maryland, Baltimore ...

Approximate linear programming (ALP) and its variants have been widely applied to Markov decision processes (MDPs) with a large number of states. A serious limitation of ALP is that it has an ...

AccelChip Offers Linear Algebra Cores through Xilinxs Alliance Program MILPITAS, CA, July 27, 2005 AccelChip Inc., the industrys only provider of automated flows from MATLAB algorithms to silicon, has ...