Convergent Lagrangian heuristics for nonlinear minimum cost network flows

Convergent Lagrangian heuristics for nonlinear minimum cost network flows

We consider the separable nonlinear and strictly convex single-commodity network flow problem (SSCNFP). We develop a computational scheme for generating a primal feasible solution from any Lagrangian dual vector; this is referred to as “early primal recovery”. It is motivated by the desire to obtain a primal feasible vector before convergence of a Lagrangian scheme; such a vector is not availab...

Abstraction Heuristics, Cost Partitioning and Network Flows

ion Heuristics, Cost Partitioning and Network Flows Florian Pommerening and Malte Helmert University of Basel, Switzerland {florian.pommerening, malte.helmert}@unibas.ch Blai Bonet Universidad Simón Bolívar, Caracas, Venezuela [email protected]

Minimum Convex Cost Dynamic Network Flows

This paper presents and solves in polynomial time the minimum convex cost dynamic network flow problem, an infinite horizon integer programming problem which involves network flows evolving over time. The model is a finite network in which each arc has an associated transit time for flow to pass through it. An integral amount of flow is to be sent through arcs of the network in each period over...

Minimum cost capacity installation for multicommodity network flows

Consider a directed graph G = (V; A), and a set of traac demands to be shipped between pairs of nodes in V. Capacity has to be installed on the edges of this graph (in integer multiples of a base unit) so that traac can be routed. In this paper we consider the problem of minimum cost installation of capacity on the arcs to ensure that the required demands can be shipped simultaneously between n...

Minimum cost flows