Time Dependent Fleet Size And Mix Location Routing Problem
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Time Dependent Fleet Size And Mix Location Routing Problem
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Author : Carise E. Schmidt
language : en
Publisher:
Release Date : 2020
Time Dependent Fleet Size And Mix Location Routing Problem written by Carise E. Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Time Dependent Fleet Size And Mix Location Routing Problem
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Author : Carise E Schmidt
language : en
Publisher:
Release Date : 2020
Time Dependent Fleet Size And Mix Location Routing Problem written by Carise E Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
The Fleet Size And Mix Location Routing Problem With Time Windows
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Author : Çagri Koç
language : en
Publisher:
Release Date : 2015
The Fleet Size And Mix Location Routing Problem With Time Windows written by Çagri Koç and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Delivering In Congested Urban Environments The Benefits Of Several Depots And A Diverse Fleet
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Author : Carise E. Schmidt
language : en
Publisher:
Release Date : 2022
Delivering In Congested Urban Environments The Benefits Of Several Depots And A Diverse Fleet written by Carise E. Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 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.
The Fleet Size And Mix Vehicle Routing Problem
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Author : Larry Jay Levy
language : en
Publisher:
Release Date : 1980
The Fleet Size And Mix Vehicle Routing Problem written by Larry Jay Levy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with categories.
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.
New Heuristics For The Fleet Size And Mix Vehicle Routing Problem With Time Windows
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Author : Wout Dullaert
language : en
Publisher:
Release Date : 2001
New Heuristics For The Fleet Size And Mix Vehicle Routing Problem With Time Windows written by Wout Dullaert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Alternative Formulations And Improved Bounds For The Multi Depot Fleet Size And Mix Vehicle Routing
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Author : Rahma Lahyani
language : en
Publisher:
Release Date : 2015
Alternative Formulations And Improved Bounds For The Multi Depot Fleet Size And Mix Vehicle Routing written by Rahma Lahyani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
In this paper we model and solve the multi-depot fleet size and mix vehicle routing problem (MDFSMVRP). This problem extends the multi-depot vehicle routing problem and the fleet size and mix vehicle routing problem, two logistics problems that have been extensively studied for many decades. This difficult transportation problem combines complex assignment and routing decisions under the objective of minimizing fixed vehicle costs and variable routing costs. We first propose five distinct formulations to model the MDFSMVRP. We introduce a three-index formulation with an explicit vehicle index and a compact two-index formulation in which only vehicle types are identified. Other formulations are obtained by defining aggregated and disaggregated loading variables. The last formulation makes use of capacity-indexed variables. For each formulation, we propose sets of known and new valid inequalities to strengthen them, including symmetry breaking, lexicographic ordering, routing and rounded capacity cuts, among others. We then implement branch-and-cut and branch-and-bound algorithms for these formulations. We compare the bounds provided by the formulations on a commonly used set of instances in the MDFSMVRP literature, containing up to nine depots and 360 customers, and on newly generated instances. Our in-depth analysis of the five formulations shows which formulations tend to perform better on each type of instance. Moreover, we have considerably improved the lower bounds on all instances and significantly improved the quality of the upper bounds that can be obtained by means of currently available exact methods.--Résumé de l'éditeur.
Green Transportation And New Advances In Vehicle Routing Problems
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Author : Houda Derbel
language : en
Publisher: Springer Nature
Release Date : 2020-12-08
Green Transportation And New Advances In Vehicle Routing Problems written by Houda Derbel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-08 with Computers categories.
This book presents recent work that analyzes general issues of green transportation. The contributed chapters consider environmental objectives in transportation, including topics such as battery swap stations for electric vehicles, efficient home healthcare routing, waste collection, and various vehicle routing problems. The content will be valuable for researchers and postgraduate students in computer science, operations research, and urban planning.