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Network planning and design

About: Network planning and design is a research topic. Over the lifetime, 12393 publications have been published within this topic receiving 229776 citations. The topic is also known as: network design.


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Journal ArticleDOI
TL;DR: This paper studies two core subproblems of the NLP: a three node network and a multiple commodity, single arc capacitated network design problem; in both cases, families of facets are developed and completely characterize the convex hull of feasible solutions to the integer programming formulation of the problems.
Abstract: The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed point-to-point demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs at a specified arc dependent cost. The problem is to determine the number of facilities to be loaded on the arcs that will satisfy the given demand at minimum cost.

171 citations

Proceedings ArticleDOI
12 Nov 2000
TL;DR: This work introduces a new version of the facility location problem: one in which every open facility is required to have some minimum amount of demand assigned to it, and presents a simple bicriterion approximation for this problem, one which is loose in both assignment cost and minimum demand, but within a constant factor of the optimum for both.
Abstract: A networking problem of present-day interest is that of distributing a single data item to multiple clients while minimizing network usage. Steiner tree algorithms are a natural solution method, but only when the set of clients requesting the data is known. We study what can be done without this global knowledge, when a given vertex knows only the probability that any other client wishes to be connected, and must simply specify a fixed path to the data to be used in case it is requested. Our problem is an example of a class of network design problems with concave cost functions (which arise when the design problem exhibits economies of scale). In order to solve our problem, we introduce a new version of the facility location problem: one in which every open facility is required to have some minimum amount of demand assigned to it. We present a simple bicriterion approximation for this problem, one which is loose in both assignment cost and minimum demand, but within a constant factor of the optimum for both. This suffices for our application. We leave open the question of finding an algorithm that produces a truly feasible approximate solution.

170 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the benefit distribution among the network users and the resulting equity associated with the continuous network design problem in terms of the change of equilibrium O-D travel costs.
Abstract: In the classical continuous network design problem, the optimal capacity enhancements are determined by minimizing the total system cost under a budget constraint, while taking into account the route choice behavior of network users. Generally the equilibrium origin–destination travel costs for some origin–destination (O–D) pairs may be increased after implementing these optimal capacity enhancements, leading to positive or negative results for network users. Therefore, the equity issue about the benefit gained from the network design problem is raised. In this paper, we examine the benefit distribution among the network users and the resulting equity associated with the continuous network design problem in terms of the change of equilibrium O–D travel costs. Bilevel programming models that incorporate the equity constraint are proposed for the continuous network design problem. A penalty function approach by embodying a simulated annealing method is used to test the models for a network example.

170 citations

Journal ArticleDOI
TL;DR: A new content-based, non-intrusive quality of experience (QoE) prediction model for low bitrate and resolution (QCIF) H.264 encoded videos and its application in video quality adaptation over Universal Mobile Telecommunication Systems (UMTS) networks is illustrated.
Abstract: The primary aim of this paper is to present a new content-based, non-intrusive quality of experience (QoE) prediction model for low bitrate and resolution (QCIF) H.264 encoded videos and to illustrate its application in video quality adaptation over Universal Mobile Telecommunication Systems (UMTS) networks. The success of video applications over UMTS networks very much depends on meeting the QoE requirements of users. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet such QoE requirements. Video quality is affected by distortions caused both by the encoder and the UMTS access network. The impact of these distortions is content dependent, but this feature is not widely used in non-intrusive video quality prediction models. In the new model, we chose four key parameters that can impact video quality and hence the QoE-content type, sender bitrate, block error rate and mean burst length. The video quality was predicted in terms of the mean opinion score (MOS). Subjective quality tests were carried out to develop and evaluate the model. The performance of the model was evaluated with unseen dataset with good prediction accuracy ( ~ 93%). The model also performed well with the LIVE database which was recently made available to the research community. We illustrate the application of the new model in a novel QoE-driven adaptation scheme at the pre-encoding stage in a UMTS network. Simulation results in NS2 demonstrate the effectiveness of the proposed adaptation scheme, especially at the UMTS access network which is a bottleneck. An advantage of the model is that it is light weight (and so it can be implemented for real-time monitoring), and it provides a measure of user-perceived quality, but without requiring time-consuming subjective tests. The model has potential applications in several other areas, including QoE control and optimization in network planning and content provisioning for network/service providers.

169 citations

Journal ArticleDOI
TL;DR: This paper considers the trade-off between inventory cost, direct shipment cost, and facility location cost in such a system and shows that the moderate size distribution network design problem can be solved efficiently via this approach.
Abstract: In this paper, we study the distribution network design problem integrating transportation and infinite horizon multiechelon inventory cost function. We consider the trade-off between inventory cost, direct shipment cost, and facility location cost in such a system. The problem is to determine how many warehouses to set up, where to locate them, how to serve the retailers using these warehouses, and to determine the optimal inventory policies for the warehouses and retailers. The objective is to minimize the total multiechelon inventory, transportation, and facility location costs. To the best of our knowledge, none of the papers in the area of distribution network design has explicitly addressed the issues of the 2-echelon inventory cost function arising from coordination of replenishment activities between the warehouses and the retailers. We structure this problem as a set-partitioning integer-programming model and solve it using column generation. The pricing subproblem that arises from the column generation algorithm gives rise to a new class of the submodular function minimization problem. We show that this pricing subproblem can be solved inO( n?log? n) time, wheren is the number of retailers. Computational results show that the moderate size distribution network design problem can be solved efficiently via this approach.

169 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202390
2022195
2021432
2020493
2019570
2018573