Download or read book Solution Algorithms for Resource and Route Constrained Shortest Path Problems in Time dependent Transportation Networks written by Erkut Yucaoğlu and published by . This book was released on 1973 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Solution Algorithms for Resource and Route Constrained Shortest Path Problems in Time dependent Transportation Networks written by Erkut Yucaoğlu and published by . This book was released on 1973 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Column Generation written by Guy Desaulniers and published by Springer Science & Business Media. This book was released on 2006-03-20 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Column Generation is an insightful overview of the state of the art in integer programming column generation and its many applications. The volume begins with "A Primer in Column Generation" which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on "Shortest Path Problems with Resource Constraints," "Vehicle Routing Problem with Time Window," "Branch-and-Price Heuristics," "Cutting Stock Problems," each dealing with methodological aspects of the field. Three chapters deal with transportation applications: "Large-scale Models in the Airline Industry," "Robust Inventory Ship Routing by Column Generation," and "Ship Scheduling with Recurring Visits and Visit Separation Requirements." Production is the focus of another three chapters: "Combining Column Generation and Lagrangian Relaxation," "Dantzig-Wolfe Decomposition for Job Shop Scheduling," and "Applying Column Generation to Machine Scheduling." The final chapter by François Vanderbeck, "Implementing Mixed Integer Column Generation," reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).

Download or read book Time dependent Routing written by Rabie Jaballah and published by . This book was released on 2022 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The vehicle routing problem (VRP), introduced more than 60 years ago, is at the core of transportation systems. With decades of development, the VRP is one of the most studied problems in the literature, with a very rich set of variants. Yet, primarily due to the lack of data, two critical assumptions make the VRP fail to adapt effectively to traffic and congestion. The first assumption considers that the travel speed is constant over time ; the second, that each pair of customers is connected by an arc, ignoring the underlying street network. Traffic congestion is one of the biggest challenges in transportation systems. As traffic directly affects transportation activities, the whole supply chain needs to adjust to this factor. The continuous growth of freight in recent years worsens the situation, and a renewed focus on mobility, environment, and city logistics has shed light on these issues. Recently, advances in communications and real-time data acquisition technologies have made it possible to collect vehicle data such as their location, acceleration, driving speed, deceleration, etc. With the availability of this data, one can question the way we define, model, and solve transportation problems. This allows us to overcome the two issues indicated before and integrate congestion information and the whole underlying street network. We start by considering the whole underlying street network, which means we have customer nodes and intermediate nodes that constitute the street network. Then, we model the travel time of each street during the day. By dividing the day into small intervals, up to a precision of a second, we consider precise traffic information. This results in a new problem called the time-dependent shortest path vehicle routing problem (TD-SPVRP), in which we combine the time-dependent shortest path problem (TD-SPP) and the time-dependent VRP (TD-VRP), creating a more general and very challenging problem. The TD-SPVRP is closer to what can be found in real-world conditions, and it constitutes the topic of Chapter 2, where we formulate it as a mixed-integer linear programming model and design a fast and efficient heuristic algorithm to solve this problem. We test it on instances generated from actual traffic data from the road network in Québec City, Canada. Results show that the heuristic provides high-quality solutions with an average gap of only 5.66%, while the mathematical model fails to find a solution for any real instance. To solve the challenging problem, we emphasize the importance of a high-performance implementation to improve the speed and the execution time of the algorithms. Still, the problem is huge especially when we work on a large area of the underlying street network alongside very precise traffic data. To this end, we use different techniques to optimize the computational effort to solve the problem while assessing the impact on the precision to avoid the loss of valuable information. Two types of data aggregation are developed, covering two different levels of information. First, we manipulated the structure of the network by reducing its size, and second by controlling the time aggregation level to generate the traffic data, thus the data used to determine the speed of a vehicle at any time. For the network structure, we used different reduction techniques of the road graph to reduce its size. We studied the value and the trade-off of spatial information. Solutions generated using the reduced graph are analyzed in Chapter 3 to evaluate the quality and the loss of information from the reduction. We show that the transformation of the TD-SPVRP into an equivalent TD-VRP results in a large graph that requires significant preprocessing time, which impacts the solution quality. Our development shows that solving the TD-SPVRP is about 40 times faster than solving the related TD-VRP. Keeping a high level of precision and successfully reducing the size of the graph is possible. In particular, we develop two reduction procedures, node reduction and parallel arc reduction. Both techniques reduce the size of the graph, with different results. While the node reduction leads to improved reduction in the gap of 1.11%, the parallel arc reduction gives a gap of 2.57% indicating a distortion in the reduced graph. We analyzed the compromises regarding the traffic information, between a massive amount of very precise data or a smaller volume of aggregated data with some potential information loss. This is done while analyzing the precision of the aggregated data under different travel time models, and these developments appear in Chapter 4. Our analysis indicates that a full coverage of the street network at any time of the day is required to achieve a high level of coverage. Using high aggregation will result in a smaller problem with better data coverage but at the cost of a loss of information. We analyzed two travel time estimation models, the link travel model (LTM) and the flow speed model (FSM). They both shared the same performance when working with large intervals of time (120, 300, and 600 seconds), thus a higher level of aggregation, with an absolute average gap of 5.5% to the observed route travel time. With short periods (1, 10, 30, and 60 seconds), FSM performs better than LTM. For 1 second interval, FSM gives an average absolute gap of 6.70%, while LTM provides a gap of 11.17%. This thesis is structured as follows. After a general introduction in which we present the conceptual framework of the thesis and its organization, Chapter 1 presents the literature review for the two main problems of our development, the shortest path problem (SPP) and the VRP, and their time-dependent variants developed over the years. Chapter 2 introduces a new VRP variant, the TD-SPVRP. Chapter 3 presents the different techniques developed to reduce the size of the network by manipulating spatial information of the road network. The impact of these reductions is evaluated and analyzed on real data instances using multiple heuristics. Chapter 4 covers the impact of time aggregation data and travel time models when computing travel times on the precision of their estimations against observed travel times. The conclusion follows in the last chapter and presents some research perspectives for our works.

Download or read book Robust and Online Large Scale Optimization written by Ravindra K. Ahuja and published by Springer. This book was released on 2009-10-21 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scheduled transportation networks give rise to very complex and large-scale networkoptimization problems requiring innovative solution techniques and ideas from mathematical optimization and theoretical computer science. Examples of scheduled transportation include bus, ferry, airline, and railway networks, with the latter being a prime application domain that provides a fair amount of the most complex and largest instances of such optimization problems. Scheduled transport optimization deals with planning and scheduling problems over several time horizons, and substantial progress has been made for strategic planning and scheduling problems in all transportation domains. This state-of-the-art survey presents the outcome of an open call for contributions asking for either research papers or state-of-the-art survey articles. We received 24 submissions that underwent two rounds of the standard peer-review process, out of which 18 were finally accepted for publication. The volume is organized in four parts: Robustness and Recoverability, Robust Timetabling and Route Planning, Robust Planning Under Scarce Resources, and Online Planning: Delay and Disruption Management.

Download or read book A Computational Study of Routing Algorithms for Realistic Transportation Networks written by and published by . This book was released on 1998 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors 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 and exact solutions, associated data structures affected the computational performance of the software developed especially for realistic transportation networks. For this purpose the authors have used Dallas Fort-Worth road network with very high degree of resolution. The following general results are obtained: (1) they discuss and experimentally analyze various one-one shortest path algorithms, which 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; (2) they describe a number of extensions to the basic shortest path algorithm. These extensions were primarily motivated by practical problems arising in TRANSIMS and ITS (Intelligent Transportation Systems) related technologies. Extensions discussed include--(i) time dependent networks, (ii) multi-modal networks, (iii) networks with public transportation and associated schedules. Computational results are provided to empirically compare the efficiency of various algorithms. The studies indicate that a modified Dijkstra's algorithm is computationally fast and an excellent candidate for use in various transportation planning applications as well as ITS related technologies.

Download or read book The Shortest Path Problem written by Hector Ortega-Arranz and published by Springer Nature. This book was released on 2022-05-31 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many applications in different domains need to calculate the shortest-path between two points in a graph. In this paper we describe this shortest path problem in detail, starting with the classic Dijkstra's algorithm and moving to more advanced solutions that are currently applied to road network routing, including the use of heuristics and precomputation techniques. Since several of these improvements involve subtle changes to the search space, it may be difficult to appreciate their benefits in terms of time or space requirements. To make methods more comprehensive and to facilitate their comparison, this book presents a single case study that serves as a common benchmark. The paper also compares the search spaces explored by the methods described, both from a quantitative and qualitative point of view, and including an analysis of the number of reached and settled nodes by different methods for a particular topology. Table of Contents: List of Figures / List of Tables / Acknowledgments / Introduction / Graph Theory Basics / Classical Algorithms / Hierarchical Preprocessing-Dependent Approaches / Non-Hierarchical Preprocessing-Dependent Approaches / Analysis and Comparison of Approaches / Conclusions / Bibliography / Authors' Biographies

Download or read book UMTA University Research and Training Program written by United States. Urban Mass Transportation Administration. University Research and Training Division and published by . This book was released on 1968 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Reliable Shortest Path Problems in Networks Under Uncertainty written by Biyu Chen and published by . This book was released on 2012 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed RSP model and solution algorithm are extended to incorporate travel time temporal correlations in those stochastic time-dependent (STD) networks where link travel time distributions vary by time intervals throughout the day. In the STD networks, travellers' experienced link travel time variation depends on the time instance vehicles entering the link; and the link travel time distribution is typically assumed to be fixed when these vehicles travelling on that link. This assumption, however, may violate the first in first out (FIFO) property, since traffic conditions cannot be updated when vehicles travelling on the link. To address this non-FIFO problem, a stochastic travel speed model (S-TSM) that can update travellers' experienced travel speeds during different time intervals on the link is proposed in this research. The proposed S-TSM can ensure the FIFO property of link travel times, so that the efficient multi-criteria A* algorithm can be adopted to solve the RSP problems in STD networks. Based on the proposed multi-criteria A* algorithm, a real-world ATIS-based routing system is developed to aid road users of Hong Kong making route choice decisions in road networks with travel time spatiotemporal correlations. Secondly, the proposed RSP model is incorporated in reliability-based user equilibrium (RUE) problems for traffic assignment. In this research, an effective reliable shortest path algorithm is developed to determine RSP for all user classes in one search process so as to avoid the repeated path searching for each user class. The proposed reliable shortest path algorithm is then, further incorporated into a path-based RUE assignment algorithm using a column generation method. The proposed RUE assignment algorithm does not require path enumeration and can achieve highly accurate RUE results within reasonable computational time. A numerical example demonstrates that the proposed RUE assignment algorithm is capable for solving relevant problems in road networks with demand and / or supply uncertainties. Thirdly, the proposed RSP and RUE algorithms are applied to identify critical links in large-scale road networks. The traditional method, to identify critical links, is to use a full scan approach to assess all possible link closure scenarios by means of traffic assignment methods. This full scan approach is not viable for identifying critical links in large-scale road networks, because of the large number of link closure scenarios and computational intensity of traffic assignment methods in these large-scale networks. An impact area vulnerability analysis approach is proposed in this research to evaluate the consequences of a link failure within a local impact area, rather than the entire network. Such vulnerability analysis approach reduces the problem size of the critical link identification so as to reduce the computational burden involved. Case studies on large-scale real-world networks are presented to illustrate the proposed impact area vulnerability approach and investigate the effects of stochastic demand and heterogeneous travellers' risk-taking behaviour.

Download or read book An Exact Algorithm for the Elementary Shortest Path Problem with Resource Constraints Application to Some Vehicle Routing Problems written by Guéguen, Cyrille and published by Montréal : Centre for Research on Transportation = Centre de recherche sur les transports (C.R.T.). This book was released on 2000 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis and Design of a Transportation Information Center written by Randolph F. Buckley and published by . This book was released on 1973 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Capacity Constrained Routing Algorithms for Evacuation Route Planning written by Qingsong Lu and published by . This book was released on 2006 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evacuation route planning identifies paths in a given transportation network to minimize the time needed to move vulnerable populations to safe destinations. Evacuation route planning is critical for numerous important applications like disaster emergency management and homeland defense preparation. It is computationally challenging because the number of evacuees often far exceeds the capacity, i.e. the number of people that can move along the road segments in a unit time. Linear Programming(LP) based methods using time expanded networks can take hours to days of computation for metropolitan sized problems. In this paper, we propose a new approach, namely a capacity constrained routing planner which models capacity as a time series and generalizes shortest path algorithms to incorporate capacity constraints. We characterize the design space for reducing the computational cost. Analytical cost model and experiment results show that the proposed algorithm is faster than the LP based algorithms and requires less memory. Experimental evaluation using various network configurations also shows that the proposed algorithm produces solutions that are comparable to those produced by LP based algorithms while significantly reducing the computational cost.

Download or read book Time dependent Networks written by Vinay Muralidhara Yadappanavar and published by . This book was released on 2000 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Government Reports Announcements written by and published by . This book was released on 1974 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book UMTA University Research and Training Program written by United States. Urban Mass Transportation Administration. University Research and Training Division and published by . This book was released on 1978 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time Constrained Shortest Paths in Stochastic and Dynamic Transportation Networks written by Deepak Kumar and published by . This book was released on 2004 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops methodologies for solving constrained shortest path problems in dynamic and random conditions. Due to the randomness of the network, the decisions need to account for uncertainty of the future real-time network state. Currently the randomness of the arc attributes is not taken into consideration. In this thesis, the intent is to develop methodologies for finding best paths when the arc attributes are uncertain, and change with time. Modified label correcting algorithms are developed for several new variations of the constrained stochastic dynamic shortest path problem where the objective is to minimize the expected cost subject to a specified constraint on the travel time of the path. The constraint can be placed on the expected travel time of the path, or on the cumulative probability of experiencing a maximum travel time. Unlike deterministic networks, in which a single minimum cost path can be determined between an origin and a destination, several paths may each have some positive probability of having the least cost for some realization of the network when the arc times and costs are stochastic and thus, a set of Pareto-optimal paths can be generated. Multiple variations are also examined when considering the FIFO nature of travel times in the network. The correctness of the proposed algorithms is proved. Extensive numerical experiments are conducted to access the performance of these procedures. Also some of the instances are discussed where this problem has practical significance

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2007 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt: