O problema de caminho mínimo com incertezas e restrições de tempo

Abstract

O problema de caminho mínimo em grafos com parâmetros incertos é um importante problema da programação matemática, visto que possui aplicações nas mais diversas áreas da Computação e da Engenharia, como: redes de computadores, telecomunicações, transportes, manufaturas, dentre outros. Porém, devido à sua alta complexidade computacional, poucos são os algoritmos existentes na literatura. Neste trabalho é proposto um algoritmo, baseado no algoritmo de Okada & Soper, que utiliza dois parâmetros incertos nos arcos, custo e tempo, com restrições de tempo nos nós. As incertezas são abordadas utilizando a teoria dos conjuntos fuzzy.<br>The shortest path problem in graphs with uncertainties in the parameters is an important problem in the mathematical programming, since it has a wide range of applications in different areas of Computation and Engineering, such as: computer networks, telecommunications, transportation, manufacturing, etc. However, due to its high computational complexity, there are few algorithms in the literature. In this paper is proposed an algorithm, based on Okada and Soper algorithm, which uses two uncertainty parameters, cost and time, with time restrictions in the nodes. The uncertainties are discussed using the fuzzy set theory

A method for solving linear programming models with Interval Type-2 fuzzy constraints

“…Other methods can be used for (see Almeida, Yamakami & Takahashi [1], Silva, Cantao & Yamakami [28], and Hernandes, Berto & Castanho [10]), so our proposal is just an approach to solve this kind of problems.…”

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

“…The approaches there developed solve fuzzy linear programming problems. The fuzzy set theory is applied in a different branch of optimization problems, i.e., the fuzzy graph theory to solve the minimum spanning tree problem, as described in (Almeida, 2006), and the shortest path problem, as described in (Hernandes et al, 2009). Few works focus in developing methods that solve nonlinear programming problems in fuzzy environments.…”