Abstract

During the last years, many speed-up techniques for Dijkstra 's algorithm have been developed. As a result, computing a shortest path in a staticroad network is a matter of microseconds. However, only few of those techniques work in time-dependentnetworks. Unfortunately, such networks appear frequentely in reality: Roads are predictably congestured by traffic jams, and efficient timetable information systems rely on time-dependent networks. Hence, a fast technique for routing in such networks is needed. In this work, we present an exacttime-dependent speed-up technique based on our recent SHARC-algorithm. As a result, we are able to efficiently compute shortest paths in time-dependent continental-sized transportation networks, both of roads and of railways. Document type: Part of book or chapter of book

Abstract

In Multi-Layer networks, where more than one layer is dynamic, i.e., connections are set up using not only the upper, e.g., IP layer but the underlying wavelength layer as well leads often to suboptimal performance due to long wavelength paths, that do not allow routing the traffic along the shortest path. The role of MLTE (Multi-Layer Traffic Engineering) is to cut these long wavelength paths into parts (fragments) that allow better routing at the upper layer (fragmentation), or to concatenate two or more fragments into longer paths (defragmentation) when the network load is low and therefore less hops are preferred.\r \r In this paper we present a new model (GG: Grooming Graph) and an algorithm for this model that supports Fragmentation and De-Fragmentation of wavelength paths making the network always instantly adapt to changing traffic conditions. We introduce the notion of shadow capacities to model “lightpath tailoring”. We implicitly assume that the wavelength paths carry such, e.g., IP traffic that can be interrupted for a few microseconds and that even allows minor packet reordering.\r \r To show the superior performance of our approach in various network and traffic conditions we have carried out an intensive simulation study. Document type: Part of book or chapter of book

Abstract

Traditional solutions to shortest path problems on time-varying transportation networks use traffic information only at precise moments regardless of considering the fact that the travel time through any link is dependent on the time entering that link. In this study, travel speed rather than travel time on each link is used as the time period dependent parameter to model time-dependent transportation networks, and a First-In-First-Out (FIFO) condition satisfied computational function of link travel time is then deduced based on kinematics. Finally, a temporally adaptive A* shortest path algorithm on this FIFO network is presented, where the time factor is introduced into the evaluation function, and the Euclidean distance divided by the maximum possible travel speed is used as a heuristic evaluator. An experiment on a real road network shows that the proposed algorithm is capable of foreseeing and bypassing forthcoming traffic congestion, at a cost only about 10% more in computational time than the traditional algorithm. In addition, frequent path reoptimization required with use of the traditional algorithm is effectively avoided. Document type: Part of book or chapter of book

Abstract

The conventional forwarding rule used by IP networks is to always choose the path with the shortest length – in terms of administrative link weights assigned to the links – to forward traffic. Lately, it has been proposed to use shortest-path-first routing to implement Traffic Engineering in IP networks, promising with a big boost in the profitability of the legacy network infrastructure. The idea is to set the link weights so that the shortest paths, and the traffic thereof, follow the paths designated by the operator. Unfortunately, traditional methods to calculate the link weights usually produce a bunch of superfluous shortest paths, often leading to congestion along the unconsidered paths. In this paper, we introduce and develop novel methods to increase the accuracy of this process and, by means of extensive simulations, we show that our proposed solution produces remarkably high quality link weights. Document type: Part of book or chapter of book

Abstract

In a dynamic network, the quickest path problem asks for a path minimizing the time needed to send a given amount of flow from source to sink along this path. In practical settings, for example in evacuation or transportation planning, the reliability of network arcs depends on the specific scenario of interest. In this circumstance, the question of finding a quickest path among all those having at least a desired path reliability arises. In this article, this reliable quickest path problem is solved by transforming it to the restricted quickest path problem. In the latter, each arc is associated a nonnegative cost value and the goal is to find a quickest path among those not exceeding a predefined budget with respect to the overall (additive) cost value. For both, the restricted and reliable quickest path problem, pseudopolynomial exact algorithms and fully polynomial-time approximation schemes are proposed. Document type: Part of book or chapter of book

Abstract

Part 7: Networking; International audience; In this paper, we consider the problem of finding itineraries in bus networks under multiple independent optimization criteria, namely arrival time at destination and number of transfers. It is also allowed to walk from one stop to another if the two stops are located within a small distance. A time–dependent model is proposed to solve this problem. While focusing on the network where the size of the Pareto set in the multi–criteria shortest path problem might grow exponentially, we develop an efficient algorithm with its speed–up techniques. An evaluation on the qualities of found paths and the empirical results of different implementations are given. The results show that the allowance of walking shortcuts between nearby stops gives a better route planning. Document type: Part of book or chapter of book

Abstract

The present paper focuses on the development of an algorithm for safely and optimally managing the routing of aircraft on an airport surface in future airport operations. This tool is intended to support air traffic controllers’ decision-making in selecting the paths of all aircraft and the engine startup approval time for departing ones. Optimal routes are sought for minimizing the time both arriving and departing aircraft spend on an airport surface with engines on, with benefits in terms of safety, efficiency and costs. The proposed algorithm first computes a standalone, shortest path solution from runway to apron or vice versa, depending on the aircraft being inbound or outbound, respectively. For taking into account the constraints due to other traffic on an airport surface, this solution is amended by a conflict detection and resolution task that attempts to reduce and possibly nullify the number of conflicts generated in the first phase. An example application on a simple Italian airport exemplifies how the algorithm can be applied to true-world applications. Emphasis is given on how to model an airport surface as a weighted and directed graph with non-negative weights, as required for the input to the algorithm. Document type: Article

Abstract

There is a growing market for electric vehicles (EVs) in recent years. Due to this, many studies on electric vehicles are in progress and research on charging operations for EVs are especially active. Recent research trends on electric vehicle routes rely on the stochastic modelling of various factors such as convenience of a user&rsquo s point of view, charging station (CS), location, destination, and so on. In this paper, a charging control scheme for electric vehicles is proposed from the point of view of the system operators rather than the user. From a user&rsquo s point of view, the EV route can be set up directly, but it is difficult for the system operator to directly participate in the route of the EV. In this paper, a method is proposed to indirectly change the route of the EV by changing the charging cost through real-time dynamic pricing, in order to prevent risks in the system operation due to voltage fluctuations in the system. With dynamic pricing, the voltage of the system is kept within a stable range, and the EV user sets the route with an economic benefit. The proposed scheme is verified through Dijkstra&rsquo s algorithm and a control strategy via a simulation model using MATLAB. Document type: Article