In this paper the concept of the Minimum Universal Cost Flow (MUCF) for an infeasible flow network is introduced. A new mathematical model in which the objective function includes the total costs of changing arc capacities and sending flow is built and analyzed. A polynomial time algorithm is presented to find the MUCF.

in this paper the concept of the minimum universal cost flow (mucf) for an infeasible flow network is introduced. a new mathematical model in which the objective function includes the total costs of changing arc capacities and sending flow is built and analyzed. a polynomial time algorithm is presented to find the mucf.

There are various situations in which real-world problems can be modeled and solved as minimum flow problems. Sometimes, these situations, minor data changes may occur, leading to corresponding of the networks practical problems, such slight variations capacity or lower bound. For instance, bound an arc increase decrease time, leaving one with no other choice than finding new network flow. Give...

Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function and its derivatives. Here we propose a new parameter estimation technique that does not require computing an intractable normalization factor or sampling from the equilibrium distribution of the model. This is achieved by establishing dynamics that would transform the observed da...

In the GA approach the parameters that influence its performance include population size, crossover rate and mutation rate. Genetic algorithms are suitable for traversing large search spaces since they can do this relatively fast and because the mutation operator diverts the method away from local optima, which will tend to become more common as the search space increases in size. GA’s are base...

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained pro...

in static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. in this paper, the static scheduling problem of automated guided vehicles in container terminal is solved by the network simplex algorithm (nsa). the algorithm is based on graph model and their performances are at least 100 times faster than traditional si...

Abstract The robust minimum cost flow problem under consistent constraints (RobMCF $$\equiv $$ ? ) is a new extension of the (MCF) problem. In RobMCF problem, we consider demand and supply that are subject to uncertainty. For all realizations, however, require value on an arc needs be equal if it included in ...