In network design, the gap between theory and practice is woefully broad. This book narrows it, comprehensively and critically examining current network design models and methods. You will learn where mathematical modeling and algorithmic optimization have been under-utilized. At the opposite extreme, you will learn where they tend to fail to contribute to the twin goals of network efficiency and cost-savings. Most of all, you will learn precisely how to tailor theoretical models to make them as useful as possible in practice. Throughout, the authors focus on the traffic demands encountered in the real world of network design. Their generic approach, however, allows problem formulations and solutions to be applied across the board to virtually any type of backbone communication or computer network. For beginners, this book is an excellent introduction. For seasoned professionals, it provides immediate solutions and a strong foundation for further advances in the use of mathematical modeling for network design. (Less)

Routing, Flow, And Capacity Design In Communication And Computer Networks

An analytic solution to the multi-target Bayes recursion known as the $\delta $ -Generalized Labeled Multi-Bernoulli ( $\delta $ -GLMB) filter has been recently proposed by Vo and Vo in [“Labeled Random Finite Sets and Multi-Object Conjugate Priors,” IEEE Trans. Signal Process., vol. 61, no. 13, pp. 3460–3475, 2014]. As a sequel to that paper, the present paper details efficient implementations of the $\delta $ -GLMB multi-target tracking filter. Each iteration of this filter involves an update operation and a prediction operation, both of which result in weighted sums of multi-target exponentials with intractably large number of terms. To truncate these sums, the ranked assignment and K-th shortest path algorithms are used in the update and prediction, respectively, to determine the most significant terms without exhaustively computing all of the terms. In addition, using tools derived from the same framework, such as probability hypothesis density filtering, we present inexpensive (relative to the $\delta $ -GLMB filter) look-ahead strategies to reduce the number of computations. Characterization of the $L_{1}$ -error in the multi-target density arising from the truncation is presented.

Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter

The bi-objective pollution-routing problem

The actions of autonomous vehicle manufacturers and related industrial partners, as well as the interest from policy makers and researchers, point towards the likely initial deployment of autonomous vehicles as shared autonomous mobility services. Numerous studies are lately being published regarding Shared Autonomous Vehicle (SAV) applications and hence, it is imperative to have a comprehensive outlook, consolidating the existing knowledge base. This work comprehensively consolidates studies in the rapidly emerging field of SAV. The primary focus is the comprehensive review of the foreseen impacts, which are categorised into seven groups, namely (i) Traffic & Safety, (ii) Travel behaviour, (iii) Economy, (iv) Transport supply, (v) Land–use, (vi) Environment & (vii) Governance. Pertinently, an SAV typology is presented and the components involved in modelling SAV services are described. Issues relating to the expected demand patterns and a required suitable policy framework are explicitly discussed.

/pdf/shared-autonomous-vehicle-services-a-comprehensive-review-qacqjg2kag.pdf

Shared autonomous vehicle services: A comprehensive review

There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by concerns for the environment and also new developments in technologies which enable new modes of operations. This paper surveys the research developments on the Dial-A-Ride Problem (DARP) since 2007. We provide a classification of the problem variants and the solution methodologies, and references to benchmark instances. We also present some application areas for the DARP, discuss some future trends and challenges, and indicate some possible directions for future research.

A survey of dial-a-ride problems: Literature review and recent developments

Yen’s algorithm is a classical algorithm for ranking the K shortest loopless paths between a pair of nodes in a network. In this paper an implementation of Yen’s algorithm is presented. Both the original algorithm and this implementation present ${\cal O}(Kn(m + n\log n))$
 computational complexity order when considering a worst-case analysis. However, computational experiments are reported, which allow to conclude that in practice this new implementation outperforms two other, Perko’s implementation and a straightforward one.

https://estudogeral.sib.uc.pt/bitstream/10316/7763/1/obra.pdf

A new implementation of Yen’s ranking loopless paths algorithm

The shortest path problem is a classical network problem that has been extensively studied. The problem of determining not only the shortest path, but also listing the K shortest paths (for a given integer K>1) is also a classical one but has not been studied so intensively, despite its obvious practical interest. Two different types of problems are usually considered: the unconstrained and the constrained K shortest paths problem. While in the former no restriction in considered in the definition of a path, in the constrained K shortest paths problem all the paths have to satisfy some condition – for example, to be loopless. In this paper new algorithms are proposed for the uncontrained problem, which compute a super set of the K shortest paths. It is also shown that ranking loopless paths does not hold in general the Optimality Principle and how the proposed algorithms for the unconstrained problem can be adapted for ranking loopless paths.

Deviation algorithms for ranking shortest paths

In the Dial-a-Ride Problem (DARP) the aim is to design vehicle routes for a set of users who must be transported between given origin and destination pairs, subject to a variety of side constraints. The standard DARP objective is cost minimization. In addition to cost, the objectives considered in this paper include three terms related to quality of service. This gives rise to a multicriteria problem. The problem is solved by means of a flexible and simple metaheuristic which efficiently integrates the reference point method for multicriteria optimization within a tabu search mechanism. Extensive tests were performed on randomly generated data and on real-life data provided by a major transporter in the Montreal area. Results indicate that the algorithm can yield a rich set of non-dominated solutions. It can also be employed to determine good trade-offs between cost and quality of service.

/pdf/combining-multicriteria-analysis-and-tabu-search-for-dial-a-1t2gxylhmv.pdf

Combining multicriteria analysis and tabu search for dial-a-ride problems

https://estudogeral.sib.uc.pt/bitstream/10316/5485/1/filee29acc81ac9343228be10f615af717d4.pdf

Internet packet routing: Application of a K-quickest path algorithm

https://estudogeral.sib.uc.pt/bitstream/10316/4102/1/file93575488f5ae462fb81c859da64d03dc.pdf

Marta M. B. Pascoal

Papers

A new implementation of Yen’s ranking loopless paths algorithm

Deviation algorithms for ranking shortest paths

Combining multicriteria analysis and tabu search for dial-a-ride problems

Internet packet routing: Application of a K-quickest path algorithm

An algorithm for ranking quickest simple paths