We carry out an experimental analysis of a number of shortest path (routing) algorithms investigated in the context of the TRANSIMS (TRansportation ANalysis and SIMulation System) project. The main focus of the paper is to study how various heuristic as well as exact solutions and associated data structures affect the computational performance of the software developed for realistic transportation networks. For this purpose we have used a road network representing with high degree of resolution the Dallas Ft-Worth urban area. We discuss and experimentally analyze various one-to-one shortest path algorithms. These include classical exact algorithms studied in the literature as well as heuristic solutions that are designed to take into account the geometric structure of the input instances. Computational results are provided to empirically compare the efficiency of various algorithms. Our studies indicate that a modified Dijkstra's algorithm is computationally fast and an ex...

We study the algorithmic and structural properties of very large, realistic social contact networks. We consider the social network for the city of Portland, Oregon, USA, developed as a part of the TRANSIMS/EpiSims project at the Los Alamos National Laboratory. The most expressive social contact network is a bipartite graph, with two types of nodes: people and locations; edges represent people visiting locations on a typical day. Three types of results are presented. (i) Our empirical results show that many basic characteristics of the dataset are well-modeled by a random graph approach suggested by Fan Chung Graham and Lincoln Lu (the CL-model), with a power-law degree distribution. (ii) We obtain fast approximation algorithms for computing

An agent-based approach to simulation for transportation planning applications offers a lot of conceptual flexibility. Many millions of agents plus many hundreds of thousands of elements of transportation infrastructure need to be represented. For transportation planning applications, the demand needs to be sensitive to changes in supply, which implies that besides the realistic representation of the transportation system it is also necessaxy to represent people's decision-making process leading to the demand.

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In the valley-free path model, a path in a given directed graph is valid if it consists of a sequence of forward edges followed by a sequence of backward edges. This model is motivated by BGP routing policies of autonomous systems in the Internet. Robustness considerations lead to the problem of computing a maximum number of disjoint paths between two nodes, and the minimum size of a cut that separates them. We study these problems in the valley-free path model. For the problem of computing a maximum number of edge- or vertex-disjoint valid paths between two given vertices s and t, we give a 2-approximation algorithm and show that no better approximation ratio is possible unless P = NP. For the problem of computing a minimum vertex cut that separates s and t with respect to all valid paths, we give a 2-approximation algorithm and prove that the problem is APX-hard. The corresponding problem for edge cuts is shown to be polynomial-time solvable. We present additional results for acyclic graphs.

The TRANSIMS (TRansportation ANalysis and SIMulation System) project at the Los Alamos National Laboratory attempts to model all aspects of human behavior related to transportation in one consistent simulation framework. Input to TRANSIMS are transportation infrastructure data, demographic data, land-use data, and knowledge about human decision-making. Output data are any set of traditional or nontraditional measures of effectiveness (MOEs) that one could obtain from a second-by-second knowledge of the transportation system. The key to

Multi-agent transportation simulations are rule-based. The fact that such simulations do not vectorize means that the recent move to distributed computing architectures results in an explosion of computing capabilities of multiagent simulations. This paper describes the general modules which are necessary for transportation planning simulations, reports the status of an implementation of such a simulation for all of Switzerland, and gives computational performance numbers.

We consider a generalization of the point-to-point (and single-source) shortest path problem to instances where the shortest path must satisfy a formal language constraint. Given an alphabet Σ, a (directed) network G whose edges are weighted and Σ-labeled, and a regular grammar L ⊆ Σ ∗ , the Regular Language Constrained Shortest Path problem consists of finding a shortest path p in G complying with the additional constraint that l(p) ∈ L. Here l(p) denotes the unique word given by concatenating the Σ-labels of the edges along the path p. In this chapter, we summarize our recent results and present new theoretical and experimental results for the Regular Language Constrained Shortest problem. We also present extensions of several speedup techniques developed earlier for the standard point-to-point shortest path problem. These speed-up techniques are integrated within the basic algorithmic framework to yield new algorithms for the problem. In order to evaluate the performance of the basic algorithm and its extensions, we have performed preliminary experimental analysis. Through our experiments, we study the scalability of the algorithm with respect to the network size as well as with respect to the constraining language complexity. Further, we study the effectiveness of speed-up techniques such as goal-directed and bidirectional search when applied to the Regular Language Constrained Shortest problem. 1

this paper, we want to give information on how the basics of such a transportation simulation can look like. Because of our own experiences, we will focus on the TRANSIMS project; however, there are other projects in the area (e.g. [5])

Computer simulation is a computational approach whereby global system properties are produced as dynamics by direct computation of interactions among representations of local system elements. A mathematical theory of simulation consists of an account of the formal properties of sequential evaluation and composition of interdependent local mappings. When certain local mappings and their interdependencies can be related to particular real world objects and interdependencies, it is common to compute the interactions to derive a symbolic model of the global system made up of the corresponding interdependent objects. The formal mathematical and computational account of the simulation provides a particular kind of theoretical explanation of the global system properties and, therefore, insight into how to engineer a complex system to exhibit those properties. This paper considers the mathematical foundations and engineering principles necessary for building large scale simulations of socio-technical systems. Examples of such systems are urban regional transportation systems, the national electrical power markets and grid, the world-wide Internet, vaccine design and deployment, theater war, etc. These systems are composed of large numbers of interacting human, physical and technological components. Some components adapt and learn, exhibit perception, interpretation, reasoning, deception, cooperation and non-cooperation, and economic motives as well as the usual physical properties of interaction. The systems themselves are large and the behavior of sociotechnical systems is tremendously complex.