Real Time Vehicle Routing In Large Networks
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Real Time Vehicle Routing In Large Networks
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Author : Laia Pagès Giralt
language : en
Publisher: VDM Publishing
Release Date : 2007
Real Time Vehicle Routing In Large Networks written by Laia Pagès Giralt and has been published by VDM Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematical optimization categories.
The problems treated in this book are very simple in nature: how to route n vehicles in real time in a fast varying environment to pickup and deliver m passengers when both n and m are large? These problems are very relevant to future transportation options involving large scale real-time routing of shared-ride fleet transit vehicles. But, even if the nature of these problems looks so simple, solving them is not so straight forward, specially finding fast and reliable solutions. Traditionally, dynamic routing solutions were found as static approximations for smaller-scale problems or using local heuristics for the larger-scale ones. Generally heuristics used for these types of problems do not consider global optimality. This work develops a hierarchical methodology to solve these types of problems in three stages seeking global optimality. The book first introduces the problems treated, secondly presents the main characteristics of the proposed methodology, followed by insights on each of the proposed stages. Then a general framework to use the proposed methodology for any vehicle routing problem is presented. Finally, a real application is presented. The work is addressed to professionals and researchers working on vehicle routing and network optimization issues.
Real Time Mass Transport Vehicle Routing Problem Hierarchical Global Optimization For Large Networks
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Author : Laia Pagès
language : en
Publisher:
Release Date : 2006
Real Time Mass Transport Vehicle Routing Problem Hierarchical Global Optimization For Large Networks written by Laia Pagès and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Transportation engineering categories.
The thesis presents the proposed methodology, gives insights on each of the proposed stages, develops a general framework to use the proposed methodology to solve any VRP and presents an application through microsimulation for the city of Barcelona in Spain.
Time Dependent Routing
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Author : Rabie Jaballah
language : en
Publisher:
Release Date : 2022
Time Dependent Routing written by Rabie Jaballah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Business logistics categories.
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.
Pro Active Dynamic Vehicle Routing
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Author : Francesco Ferrucci
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Pro Active Dynamic Vehicle Routing written by Francesco Ferrucci and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Business & Economics categories.
This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.
Advanced Methods In Transportation Analysis
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Author : Lucio Bianco
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Advanced Methods In Transportation Analysis written by Lucio Bianco and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
This volume is a compendium of papers presented during the second TRlennal Symposium on Transportation ANalysis (TRISTAN II) that took place in Capri, Italy on June 23-28, 1994. The Symposium was organized by the Progetto Finalizzato Trasporti and the Istituto di Analisi dei Sistemi ed Informatica of the Italian National Research Council jointly with the Italian Operations Research Society. The purpose of this kind of meetings is to periodically allow an exchange of views and findings by scientists in the field of transportation analysis methods and tools. Therefore, the papers presented dealt with a wide range of topics and cover the different aspects of transportation analysis. The material contained in this book gives particular emphasis to the development of mathematical modelling and algorithms. This development is due to the evolution of digital computers and the continuous increase of the computing power. In fact the need of solving large scale problems (crew scheduling, network traffic control, pollution monitoring and control,. etc ... ) involves in some case, thousands of variables and therefore sophisticated mathematical models and computational algorithms.
Real Time Vehicle Routing And Scheduling In Dynamic And Stochastic Traffic Networks
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Author : Liping Fu
language : en
Publisher:
Release Date : 1996
Real Time Vehicle Routing And Scheduling In Dynamic And Stochastic Traffic Networks written by Liping Fu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
Conflict Free Vehicle Routing With An Application To Personal Rapid Transit
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Author : Kaspar Schüpbach
language : en
Publisher: Cuvillier Verlag
Release Date : 2012-09-04
Conflict Free Vehicle Routing With An Application To Personal Rapid Transit written by Kaspar Schüpbach and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-04 with Mathematics categories.
This thesis investigates the conflict-free routing of vehicles through a track network, a problem frequently encountered in many applications in transportation and logistics. The most common routing approach for conflictfree routing problems in various settings is a sequential one, where requests are greedily served one after the other in a quickest way without interfering with previously routed vehicles. There is a need for a better theoretical understanding as guarantees on the quality of the routings are often missing. Conflict-free vehicle routing also is of inherent interest as a sister problem of the well-studied packet routing problem. In the first part, we present new theoretical results for the case of bidirectional networks. We consider a natural basic model for conflict-free routing of a set of k vehicles. Previously, no efficient algorithm is known with a sublinear (in k) approximation guarantee and without restrictions on the graph topology. We show that the conflict-free vehicle routing problem is hard to solve to optimality even on paths. Building on a sequential routing scheme, we present an algorithm for trees with makespan bounded by O(OPT) + k. Combining this result with ideas known from packet routing, we obtain a first efficient algorithm with sublinear approximation guarantee, namely an O(√k)-approximation. Additionally, a randomized algorithm leading to a makespan of O(polylog(k)) • OPT + k is presented that relies on tree embedding techniques applied to a compacted version of the graph to obtain an approximation guarantee independent of the graph size. The second part is about routing in the Personal Rapid Transit (PRT) application. PRT is a public transportation mode in which small automated vehicles transport passengers on demand. Central control of the vehicles leads to interesting possibilities for optimized routings. Routing in PRT is an online problem where transit requests appear over time and where routing decisions need to be taken without knowledge of future requests. Further, the network in PRT is directed. The complexity of the routing problems together with the fact that routing algorithms for PRT essentially have to run in real-time often leads to the choice of a fast sequential scheme. The simplicity of such schemes stems from the property that a chosen route is never changed later. This is as well the main drawback of it, potentially leading to large detours. It is natural to ask how much one could gain by using a more adaptive routing strategy. This question is one of the core motivations of this second part. We first suggest a variation to the routing model used in the first part which is suitable for PRT. We show that the routing problem remains hard in the directed setting. Further, we introduce a capacity notion for PRT networks and derive a bound for it. Computational results show that the capacity bound is close to the achievable throughput. It therefore is a useful quantity for estimating network capacity in PRT system design. We then introduce a new adaptive routing algorithm that repeatedly uses solutions to an LP as a guide to route vehicles. New requests are integrated into the LP as soon as they appear and the routing is reoptimized over all vehicles concurrently. We provide computational results that give evidence of the potential gains of an adaptive routing strategy. For this we compare the presented adaptive strategy to sequential routing and to a simple distributed routing strategy in a number of scenarios. Diese Dissertationsarbeit untersucht das konfliktfreie Befördern von Fahrzeugen durch Schienennetzwerke - eine Herausforderung, wie sie oft in verschiedensten Anwendungen in den Transport- und Logistikbranchen vorkommt. Der bekannteste Ansatz für die konfliktfreie Fahrplanung ist ein sequentieller, in dem eine Anfrage nach der anderen mit einer möglichst kurzen Reisezeit eingeplant wird, ohne mit den früheren Anfragen in Konflikt zu geraten. Solche Ansätze haben oft keine Qualitätsgarantien für den resultierenden Fahrplan, und es besteht ein Bedarf für ein besseres theoretisches Verständnis. Das Problem der konfliktfreien Fahrzeugbeförderung ist auch von Interesse durch die enge Verwandtschaft mit dem besser bekannten und untersuchten Problem der Datenbeförderung durch Kommunikationskanäle. Im ersten Teil der Dissertation präsentieren wir neue theoretische Resultate für den Fall von ungerichteten (in beiden Richtungen befahrbaren) Schienennetzwerken. Wir betrachten ein natürliches Modell für die konfliktfreie Beförderung eines Sets von k Fahrzeugen. Zuvor war kein effizienter Algorithmus mit einer sublinearen (in k) Approximationsgarantie für allgemeine Netzwerktopologien bekannt. Wir zeigen, dass es NP-schwer ist, eine optimale Lösung zu finden, sogar wenn das Netzwerk nur aus einem Pfad besteht. Wir präsentieren einen Algorithmus für Baum-Netzwerke, der auf dem sequentiellen Ansatz aufbaut und zu einem Fahrplan führt, der alle Fahrzeuge in Zeit O(OPT) + k ans Ziel befördert. Indem wir dieses Resultat mit Methoden aus dem Bereich der Datenbeförderung kombinieren, erhalten wir den ersten effizienten Algorithmus mit sublinearer Approximationsgarantie von O(√k). Zusätzlich präsentieren wir einen randomisierten Algorithmus der zu Lösungen der Länge O(polylog(k)) • OPT + k führt. Der Ansatz generiert Baumgraphen, die in eine komprimierte Version des Netzwerks eingebettet werden, womit eine Approximationsgarantie erreicht werden kann die unabhängig von der Graphgrösse ist. Der zweite Teil der Dissertation handelt von der Beförderungen von Fahrzeugen in Personal Rapid Transit (PRT). PRT ist ein öffentliches Verkehrsmittel in welchem Passagiere auf Verlangen durch kleine automatisierte Fahrzeuge befördert werden. Zentrale Steuerung der Fahrzeuge führt zu interessanten Möglichkeiten für die optimierte Nutzung der Schienenressourcen. Die Fahrplanerstellung für PRT ist ein Online-Problem in dem die Transportaufträge über die Zeit eintreffen. Entscheidungen müssen ebenfalls über die Zeit getroffen werden, ohne Kenntnis der zukünftigen Aufträge. Ein weiterer Unterschied zum ersten Teil der Dissertation ist, dass die Schienen in PRT nur in eine Richtung befahren werden. Die Komplexität des PRT Beförderungs- Problems und die Anforderung, dass die Fahrpläne in Echtzeit berechnet werden müssen, führt oft zur Wahl von schnellen sequentiellen Algorithmen. Die Einfachheit dieser Ansätze ist bedingt durch die Eigenschaft, dass ein geplanter Fahrplan nicht mehr geändert wird sobald er einmal berechnet wurde. Diese Eigenschaft ist gleichzeitig der grösste Nachteil eines solchen Ansatzes, da sie zu grossen Umwegen oder Verzögerungen führen kann. Eine natürliche Frage ist, wie viel man gewinnen kann wenn man adaptive Strategien verwendet. Diese Frage steht im Zentrum dieses zweiten Dissertationsteils. Zuerst stellen wir eine auf PRT zugeschnittene Variation des mathematischen Modells aus dem ersten Dissertationsteils vor. Wir zeigen, dass das Beförderungs-Problem auch in dieser Variante NP-schwer bleibt. Weiter führen wir einen Kapazitätsbegriff für PRT Netzwerke ein und beweisen eine obere Schranke für diese. Mit Hilfe von Simulationen können wir zeigen, dass die Kapazitätsschranke nicht weit vom erreichbaren Netzwerk-Durchsatz entfernt ist. Sie kann deshalb eine nützliche Grösse zur Abschätzung der Netzwerkkapazität in der Designphase von neuen PRT Systemen sein. Dann präsentieren wir einen neuen adaptiven Algorithmus, der den Fahrplan auf der Grundlage von LP Lösungen erstellt. Neue Aufträge werden gleich beim Eintreffen in das LP integriert und der Fahrplan wird neu berechnet, für alle Fahrzeuge gleichzeitig. Wir zeigen mit Hilfe von Simulationsresultaten das Potential solch adaptiver Strategien. Wir vergleichen den neuen adaptiven Ansatz mit dem sequentiellen Ansatz und mit einem einfachen dezentralisierten Algorithmus in einer Anzahl von Szenarien.
The Vehicle Routing Problem Latest Advances And New Challenges
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Author : Bruce L. Golden
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-20
The Vehicle Routing Problem Latest Advances And New Challenges written by Bruce L. Golden and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-20 with Business & Economics categories.
In a unified and carefully developed presentation, this book systematically examines recent developments in VRP. The book focuses on a portfolio of significant technical advances that have evolved over the past few years for modeling and solving vehicle routing problems and VRP variations. Reflecting the most recent scholarship, this book is written by one of the top research scholars in Vehicle Routing and is one of the most important books in VRP to be published in recent times.
Large Scale Transportation Routing And Mode Optimization
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Author : Yibo Dang
language : en
Publisher:
Release Date : 2020
Large Scale Transportation Routing And Mode Optimization written by Yibo Dang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Transportation categories.
In the logistics industry, many resources are spent on handling the challenges in complex transportation planning problems. The growth of e-commerce demand scalable and hybrid delivery solutions that are in-time, cost-efficient, and clean. Increased workloads demand sophisticated scheduling and routing timelines. Therefore, governments and major logistics companies are launching different programs to promote sustainable distribution processes that leverage multiple transportation modes. In this way, the transportation network costs will be decreased and the carbon efficiency will be improved. Such increasing need for detailed and multimodal plans to larger transportation problems makes the current decision support tools indispensable. The low-quality solutions and the lack of big-data capability have concerned the practitioners for a long time. The problem of routing and scheduling with different types of carriers and modes have drawn limited attentions in previous research. There is no comprehensive research that discusses implementable models and algorithms with most real-world constraints on such transportation mode decision problem. The problem implies the design of long-haul transport, efficient last-mile deliveries to fulfill the demands within in strict time windows. Because it may take several days to cover a long-haul route, it is mandatory to consider breaks or layovers during the trip. Due to the capacity limit, some non-profitable deliveries are subcontracted to third-party carriers. This strategy allows the company to fill their vehicle fleets to the maximum. To further optimize the cost and carbon efficiencies of the vehicle fleets, different types of vehicles are to be evaluated. While the traditional diesel trailers can efficiently handle large amount of cargo, the travel costs and the greenhouse gas emissions cannot be negligible. While the technologies of electric vehicles are becoming mature, the driving-range issue and the high purchase cost still worry the industry. These challenges inhibit the success of a multimodal transportation network. In this dissertation, we investigate the three related optimization problems via meta-heuristics and mathematical programming – 1) a vehicle routing problem with common carriers and time regulation (VRPCCTR), in which the working hour limit is specified and third-party common carriers’ services are considered for unprofitable deliveries; 2) an extended version of the first problem where heterogeneous-sized vehicle fleets are involved (called HVRPCCTR); 3) the electric vehicles are introduced to the problem so that the mode decision becomes determining optimal routes between mixed vehicle types and sizes (called MVRPC) observing the time windows, recharging needs, service of hours regulations, and other constraints. In short, we study a new variant of the vehicle routing problem with three shipping modes – heterogeneous internal combustion vehicles, electric vehicles, and common carriers. Our main contributions are three-fold: We propose a novel meta-heuristic algorithm called Red-Black Ant Colony System for the problems, where the black ants are searching for regular routes using different sizes of vehicles whereas the red ants re-optimize within the common carrier deliveries to build efficient dedicated fleet routes. A developed tool can solve the mode decision problem for 150,000 deliveries. And its implementation has conducted over $5 million of dollars of savings for DHL and its customers annually. For each of the three problems, we give mixed integer linear programming (MILP) models and introduce strong valid inequalities. We prove the strengths of each set of valid inequalities by analyzing the linear relaxation bounds of the models. The endeavors of reducing the symmetry in the MILP models can be seen as the complexities grow from VRPCCTR through HVRPCCTR to MVRPC. We extend our work to incorporate green transportation plans. The recharges for electric vehicles and layover needs are efficiently modeled as renewable resources. This dissertation presents the first exact method based on a branch-and-cut- and-pricing algorithm for variants of MVRPC. The algorithm is tested on real data set from small sizes to medium sizes. Its performance and sensitivity are analyzed. The results show that the our algorithm can solve the problems up to 120 customers to exact optimality. Our results provide analytical insights and implementable large-scale algorithms for multimodal transportation networks of the next-generation logistic operations. The algorithms can also be utilized to study other types of scaling networks such as social networks, electrical grid, 3D printing models, etc. Other industries, such as manufacturing, digital communication, shared economy, etc., can also benefit from our results.
Studies On Urban Vehicular Ad Hoc Networks
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Author : Hongzi Zhu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-25
Studies On Urban Vehicular Ad Hoc Networks written by Hongzi Zhu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-25 with Computers categories.
With the advancement of wireless technology, vehicular ad hoc networks (VANETs) are emerging as a promising approach to realizing "smart cities" and addressing many important transportation problems such as road safety, efficiency, and convenience. This brief provides an introduction to the large trace data set collected from thousands of taxis and buses in Shanghai, the largest metropolis in China. It also presents the challenges, design issues, performance modeling and evaluation of a wide spectrum of VANET research topics, ranging from realistic vehicular mobility models and opportunistic routing, to real-time vehicle tracking and urban sensing applications. In addition to the latest research and techniques, the reader will also learn the trace-driven methodologies and tools of performance modeling and analysis, network protocol design and optimization, and network simulation, thus keeping pace with the fast moving VANET research and development.