Algorithms for network programming

Primal-dual path-following algorithms for circular programming

Circular programming problems are a new class of convex optimization problems that include second-order cone programming problems as a special case. Alizadeh and Goldfarb [Math. Program. Ser. A 95 (2003) 3-51] introduced primal-dual path-following algorithms for solving second-order cone programming problems. In this paper, we generalize their work by using the machinery of Euclidean Jordan alg...

Fuzzy Primal Simplex Algorithms for Solving Fuzzy Linear Programming Problems

A Recurrent Neural Network Model for Solving Linear Semidefinite Programming

In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...

Algorithms for Integer Programming

• Unlike linear programming problems, integer programming problems are very difficult to solve. In fact, no efficient general algorithm is known for their solution. • Given our inability to solve integer programming problems efficiently, it is natural to ask whether such problems are inherently “hard”. Complexity theory, offers some insight on this question. It provides us with a class of probl...

Ant Programming Algorithms for Classification

Ant programming is a kind of automatic programming that generates computer programs by using the ant colony metaheuristic as the search technique. It has demonstrated good generalization ability for the extraction of comprehensible classifiers. To date, three ant programming algorithms for classification rule mining have been proposed in the literature: two of them are devoted to regular classi...