Enhanced formulations and branch-and-cut for the two level network design problem with transition facilities

2013 ◽  
Vol 225 (2) ◽  
pp. 211-222 ◽  
Author(s):  
Stefan Gollowitzer ◽  
Luis Gouveia ◽  
Ivana Ljubić
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Branch And Cut ◽  
Network Design Problem

The two-edge connected hop-constrained network design problem: Valid inequalities and branch-and-cut

Networks ◽  
2006 ◽  
Vol 49 (1) ◽  
pp. 116-133 ◽  
Author(s):  
David Huygens ◽  
Martine Labbé ◽  
A. Ridha Mahjoub ◽  
Pierre Pesneau
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Valid Inequalities ◽  
Branch And Cut ◽  
Network Design Problem

Tabu Search Algorithm for Survivable Network Design Problem with Simultaneous Unicast and Anycast Flows

2010 ◽  
Vol 56 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Jakub Gładysz ◽  
Krzysztof Walkowiak
Keyword(s):  
Tabu Search ◽  
Network Design ◽  
Design Problem ◽  
Search Algorithm ◽  
Branch And Cut ◽  
Network Design Problem ◽  
Tabu Search Algorithm ◽  
Survivable Network Design ◽  
Network Cost ◽  
Survivable Network

Tabu Search Algorithm for Survivable Network Design Problem with Simultaneous Unicast and Anycast FlowsIn this work we focus on the problem of survivable network design for simultaneous unicast and anycast flows. This problem follows from the growing popularity of network services applying the anycast paradigm. The anycasting is defined as one-to-one-of-many transmission and is applied in Domain Name Service (DNS), peer-to-peer (P2P) systems, Content Delivery Networks (CDN). In this work we formulate two models that enables joint optimization of network capacity, working and backup connections for both unicast and anycast flows. The goal is to minimize the network cost required to protect the network against failures using the single backup path approach. In the first model we consider modular link cost, in the second we are given a set of link proposal and we must select only one of them. Because these problems are NP-hard, therefore optimal solutions of branch-and-bounds or branch-and-cut methods can be generated for relatively small networks. Consequently, we propose a new heuristic algorithm based on Tabu Search method. We present results showing the effectiveness the proposed heuristic compared against optimal results. Moreover, we report results showing that the use of anycast paradigm can reduce the network cost.

A branch and cut algorithm for the hierarchical network design problem

2010 ◽  
Vol 200 (1) ◽  
pp. 28-35 ◽  
Author(s):  
Carlos Obreque ◽  
Macarena Donoso ◽  
Gabriel Gutiérrez ◽  
Vladimir Marianov
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Branch And Cut ◽  
Network Design Problem ◽  
Hierarchical Network

scholarly journals The ring/κ-rings network design problem: Model and branch-and-cut algorithm

Networks ◽  
2016 ◽  
Vol 68 (2) ◽  
pp. 130-140 ◽  
Author(s):  
Inmaculada Rodríguez-Martín ◽  
Juan-José Salazar-González ◽  
Hande Yaman
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Branch And Cut ◽  
Network Design Problem ◽  
Problem Model

Multicommodity Maximal Covering Network Design Problem for Planning Critical Routes for Earthquake Response

2003 ◽  
Vol 1857 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Kannan Viswanath ◽  
Srinivas Peeta
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Valid Inequalities ◽  
Branch And Cut ◽  
Network Design Problem ◽  
Earthquake Response ◽  
Maximal Covering ◽  
Trade Offs ◽  
Conflicting Objectives

A multicommodity maximal covering network design problem (MCNDP) is formulated for identifying critical routes for earthquake response and seismically retrofitting bridges. MCNDP seeks routes that minimize the total travel time over the selected routes and maximize the total population covered, subject to a budget constraint on bridge retrofitting costs on the selected routes. The problem is formulated as a two-objective integer programming model and solved with the branch-and-cut module in the CPLEX optimizer. The model performance is analyzed with the transportation network of a seismically prone region in southwestern Indiana. A problem reduction strategy is introduced to reduce computational times by recognizing that the critical routes usually are not circuitous. Thereby, the search for the critical routes for an origin–destination (O-D) pair is confined to a limited geographical region around it. To further reduce computational costs, the formulation is extended to incorporate valid inequalities that exploit the problem structure. Computational experiments are conducted to investigate the effects of varying the budget and the relative weights of the two objectives. Noninferior frontiers that illustrate the trade-offs between the conflicting objectives for different budgets are constructed to provide practical insights to decision makers. In addition, a vulnerability analysis is performed for the various solution instances to infer their ability to ensure connectivity between all O-D pairs after an earthquake.

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