Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm

The Minimum Universal Cost Flow in an Infeasible Flow Network

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.

An efficient implementation of a scaling minimum-cost flow algorithm

The scaling push-relabel method is an important theoretical development in the area of minimum-cost ow algorithms. We study practical implementations of this method. We are especially interested in heuristics which improve real-life performance of the method. Our implementation works very well over a wide range of problem classes. In our experiments, it was always competitive with the establish...

LagrangianHeuristics for Strictly Convex Quadratic Minimum Cost Network Flow Problems

This thesis presents a study of five different Lagrangian heuristics applied to the strictly convex quadratic minimum cost network flow problem. Tests are conducted on randomly generated transportation networks with different degrees of sparsity and nonlinearity according to a system devised by Ohuchi and Kaji [18]. The different heuristics performance in time and quality are compared. The unco...

Belief Propagation for Minimum Convex-Cost Integral Network Flow

Efficient implementations of minimum-cost flow algorithms

This paper presents efficient implementations of several algorithms for solving the minimum-cost network flow problem. Various practical heuristics and other important implementation aspects are also discussed. A novel result of this work is the application of Goldberg’s recent partial augment-relabel method in the cost-scaling algorithm. The presented implementations are available as part of t...