Simultaneous Solution of Lagrangean Dual Problems Interleaved with Preprocessing for the Weight Constrained Shortest Path Problem

Conventional Lagrangean preprocessing for the network Weight Constrained Shortest Path Problem (WCSPP calculates lower bounds on the cost of using each node and edge in a feasible path using a single optimal Lagrange multiplier for the relaxation of the WCSPP. These lower bounds are used in conjunction with an upper bound to eliminate nodes and … Read more

MOST – Multiple Objective Spanning Trees Repository Project

This article presents the Multiple Objective Spanning Trees repository – MOST – Project. As the name suggests, the MOST Project intends to maintain a repository of tests for the MOST related problems, mainly addressing real-life situations. MOST is motivated by the scarcity of repositories for the problems in the referred field. This entails difficulty in … Read more

The Maximum Flow Network Interdiction Problem: Valid Inequalities, Integrality Gaps, and Approximability

We study the Maximum Flow Network Interdiction Problem (MFNIP). We present two classes of polynomially separable valid inequalities for Cardinality MFNIP. We also prove the integrality gap of the LP relaxation of Wood’s (1993) integer program is not bounded by a constant factor, even when the LP relaxation is strengthened by our valid inequalities. Finally, … Read more

Rapidly Solving an Online Sequence of Maximum Flow Problems

We investigate how to rapidly solve an online sequence of maximum flow problems. Sequences of maximum flow problems arise in a diverse collection of settings, including stochastic network programming and real-time scheduling of jobs on a two-processor computer. In this paper, we formulate solving an online sequence of maximum flow problems as the Maximum Flow … Read more

A partitioning algorithm for the network loading problem

This paper proposes a Benders-like partitioning algorithm to solve the network loading problem. The effort of computing integer solutions is entirely left to a pure integer programming solver while valid inequalities are generated by solving standard nonlinear multicommodity flow problems. The method is compared to alternative approaches proposed in the literature and appears to be … Read more

An Interior-Point Method for Large Scale Network Utility Maximization

We describe a specialized truncated-Newton primal-dual interior-point method that solves large scale network utility maximization problems, with concave utility functions, efficiently and reliably. Our method is not decentralized, but easily scales to problems with a million flows and links. We compare our method to a standard decentralized algorithm based on dual decomposition, and show by … Read more

Dynamic Network Utility Maximization with Delivery Contracts

We consider a multi-period variation of the network utility maximization problem that includes delivery constraints. We allow the flow utilities, link capacities and routing matrices to vary over time, and we introduce the concept of delivery contracts, which couple the flow rates across time. We describe a distributed algorithm, based on dual decomposition, that solves … Read more

SNDlib 1.0–Survivable Network Design Library

We provide information on the Survivable Network Design Library (SNDlib), a data library for fixed telecommunication network design that can be accessed at http://sndlib.zib.de. In version 1.0, the library contains data related to 22 networks which, combined with a set of selected planning parameters, leads to 830 network planning problem instances. In this paper, we … Read more

On the strength of cut-based inequalities for capacitated network design polyhedra

In this paper we study capacitated network design problems, differentiating directed, bidirected and undirected link capacity models. We complement existing polyhedral results for the three variants by new classes of facet-defining valid inequalities and unified lifting results. For this, we study the restriction of the problems to a cut of the network. First, we show … Read more