Time Dependent Vehicle Routing In A Large Road Network
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Time Dependent Vehicle Routing In A Large Road Network
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Author : Zhu Zhang
language : en
Publisher:
Release Date : 2014
Time Dependent Vehicle Routing In A Large Road Network written by Zhu Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
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.
A Metaheuristic For A Time Dependent Vehicle Routing Problem With Time Windows Two Vehicle Fleets And Synchronization On A Road Network
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Author : Fernando Obed Guillen Reyes
language : en
Publisher:
Release Date : 2023
A Metaheuristic For A Time Dependent Vehicle Routing Problem With Time Windows Two Vehicle Fleets And Synchronization On A Road Network written by Fernando Obed Guillen Reyes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Managing In Real Time A Vehicle Routing Plan With Time Dependent Travel Times On A Road Network
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Author : Maha Gmira
language : en
Publisher:
Release Date : 2019
Managing In Real Time A Vehicle Routing Plan With Time Dependent Travel Times On A Road Network written by Maha Gmira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Optimization Of Time Dependent Routing Problems Considering Dynamic Paths And Fuel Consumption
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Author : Hamza Heni
language : en
Publisher:
Release Date : 2018
Optimization Of Time Dependent Routing Problems Considering Dynamic Paths And Fuel Consumption written by Hamza Heni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
In recent years, freight transportation has evolved into a multi-faceted logistics challenge. The immense volume of freight has considerably increased the flow of commodities in all transport modes. Despite the vital role of freight transportation in the economic development, it also negatively impacts both the environment and human health. At the local and regional areas, a significant portion of goods delivery is transported by trucks, which emit a large amount of pollutants. Road freight transportation is a major contributor to greenhouse gas (GHG) emissions and to fuel consumption. To reduce the significant impact of freight transportation emissions on environment, new alternative planning and coordination strategies directly related to routing and scheduling operations are required at the operational, environmental and temporal dimensions. In large urban areas, trucks must travel at the speed imposed by traffic, and congestion events have major adverse consequences on speed level, travel time and GHG emissions particularly at certain periods of day. This variability in speed over time has a significant impact on routing and scheduling. From a broader perspective, our research addresses Time-Dependent Distribution Problems (TDDPs) considering dynamic paths and GHG emissions. Considering that vehicle speeds vary according to time-dependent congestion, the goal is to minimize the total travel cost function incorporating driver and GHG emissions costs while respecting capacity constraints and service time restrictions. Further, geographical and traffic information can be used to construct a multigraph modeling path flexibility on large road networks, as an extension to the classical customers network. The underlying physical sub-network between each pair of customers for each shipment is explicitly considered to find connecting road paths. Path selection decisions complement routing ones, impacting the overall cost, GHG emissions, the travel time between nodes, and thus the set of a feasible time-dependent least cost paths. While the search space increases, solving TDDPs considering dynamic paths and time-varying speeds may provide a new scope for enhancing the effectiveness of route plans. One way to reduce emissions is to consider congestion and being able to route traffic around it. Accounting for and avoiding congested paths is possible as the required traffic data is available and, at the same time, has a great potential for both energy and cost savings. Hence, we perform a large empirical analysis of historical traffic and shipping data. Therefore, we introduce the Time-dependent Quickest Path Problem with Emission Minimization, in which the objective function comprises GHG emissions, driver and congestion costs. Travel costs are impacted by traffic due to changing congestion levels depending on the time of the day, vehicle types and carried load. We also develop time-dependent lower and upper bounds, which are both accurate and fast to compute. Computational experiments are performed on real-life instances that incorporate the variation of traffic throughout the day. We then study the quality of obtained paths considering time-varying speeds over the one based only on fixed speeds... Keywords : Time-dependent routing; time-dependent quickest paths; traffic congestion; road network; heuristic; greenhouse gas emissions; emission models; supervised learning.
Optimization Of Vehicle Routing And Scheduling With Travel Time Variability Application In Winter Road Maintenance
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Author : Haifeng Yu
language : en
Publisher:
Release Date : 2014
Optimization Of Vehicle Routing And Scheduling With Travel Time Variability Application In Winter Road Maintenance written by Haifeng Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
This study developed a mathematical model for optimizing vehicle routing and scheduling, which can be used to collect travel time information, and also to perform winter road maintenance operations (e.g., salting, plowing). The objective of this research was to minimize the total vehicle travel time to complete a given set of service tasks, subject to resource constraints (e.g., truck capacity, fleet size) and operational constraints (e.g., service time windows, service time limit). The nature of the problem is to design vehicle routes and schedules to perform the required service on predetermined road segments, which can be interpreted as an arc routing problem (ARP). By using a network transformation technique, an ARP can be transformed into a well-studied node routing problem (NRP). A set-partitioning (SP) approach was introduced to formulate the problem into an integer programming problem (I PP). To solve this problem, firstly, a number of feasible routes were generated, subject to resources and operational constraints. A genetic algorithm based heuristic was developed to improve the efficiency of generating feasible routes. Secondly, the corresponding travel time of each route was computed. Finally, the feasible routes were entered into the linear programming solver (CPL EX) to obtain final optimized results. The impact of travel time variability on vehicle routing and scheduling for transportation planning was also considered in this study. Usually in the concern of vehicle and pedestrian's safety, federal, state governments and local agencies are more leaning towards using a conservative approach with constant travel time for the planning of winter roadway maintenance than an aggressive approach, which means that they would rather have a redundancy of plow trucks than a shortage. The proposed model and solution algorithm were validated with an empirical case study of 41 snow sections in the northwest area of New Jersey. Comprehensive analysis based on a deterministic travel time setting and a time-dependent travel time setting were both performed. The results show that a model that includes time dependent travel time produces better results than travel time being underestimated and being overestimated in transportation planning. In addition, a scenario-based analysis suggests that the current NJDOT operation based on given snow sector design, service routes and fleet size can be improved by the proposed model that considers time dependent travel time and the geometry of the road network to optimize vehicle routing and scheduling. In general, the benefit of better routing and scheduling design for snow plowing could be reflected in smaller minimum required fleet size and shorter total vehicle travel time. The depot location and number of service routes also have an impact on the final optimized results. This suggests that managers should consider the depot location, vehicle fleet sizing and the routing design problem simultaneously at the planning stage to minimize the total cost for snow plowing operations.
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.
Computational Logistics
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Author : Tolga Bektaş
language : en
Publisher: Springer
Release Date : 2017-10-11
Computational Logistics written by Tolga Bektaş and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-11 with Computers categories.
This book constitutes the refereed proceedings of the 8th InternationalConference on Computational Logistics, ICCL 2017, held in Southampton,UK, in October 2017.The 38 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: vehicle routing and scheduling; maritime logistics;synchromodal transportation; and transportation, logistics and supply chain planning.
Integration Of Information And Optimization Models For Routing In City Logistics
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Author : Jan Ehmke
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-05-01
Integration Of Information And Optimization Models For Routing In City Logistics written by Jan Ehmke 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 2012-05-01 with Business & Economics categories.
As urban congestion continues to be an ever increasing problem, routing in these settings has become an important area of operations research. This monograph provides cutting-edge research, utilizing the recent advances in technology, to quantify the value of dynamic, time-dependent information for advanced vehicle routing in city logistics. The methodology of traffic data collection is enhanced by GPS based data collection, resulting in a comprehensive number of travel time records. Data Mining is also applied to derive dynamic information models as required by time-dependent optimization. Finally, well-known approaches of vehicle routing are adapted in order to handle dynamic information models. This book interweaves the usually distinct areas of traffic data collection, information retrieval and time-dependent optimization by an integrated methodological approach, which refers to synergies of Data Mining and Operations Research techniques by example of city logistics applications. These procedures will help improve the reliability of logistics services in congested urban areas.
Time Dependent Vehicle Routing Problem With Emission And Cost Minimization Considering Dynamic Paths
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Author : Hamza Heni
language : en
Publisher:
Release Date : 2018
Time Dependent Vehicle Routing Problem With Emission And Cost Minimization Considering Dynamic Paths written by Hamza Heni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.