Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit ...

A method is described for converting a boolean expression to a disjunctive normal equivalent (two level OR-AND circuit) which is minimal under some criterion presented in advance, as for example, the ...

Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function.

The LPS is a package is used for solving a linear programming problem, it is capable of handling of minimization was well as maximization problems. It uses two phase simplex method to solve linear ...

Markov random fields with higher order potentials have emerged as a powerful model for several problems in computer vision. In order to facilitate their use, we propose a new representation for higher ...

This project is aimed at implementing nonlinear programming algorithms as the (un-)constrained minimization problems with the focus on their numerical expression using various programming languages.

To solve an Integer Programming problem, we can use the Branch and Bound algorithm: # IP: a minimization integer program with constraints and objective function cost def branch_and_bound(IP): 1. Push ...

In this paper, we presented a new integer programming model for the Minimization of Open Stacks Problem (MOSP). It is based on the edge completion of a MOSP graph (to obtain an interval graph) and on ...