The Pyramidal Capacitated Vehicle Routing Problem
Lysgaard, Jens
This paper introduces the Pyramidal Capacitated Vehicle Routing Problem (PCVRP) as a restricted version of the Capacitated Vehicle Routing Problem (CVRP). In the PCVRP each route is required to be pyramidal in a sense generalized from the Pyramidal Traveling Salesman Problem (PTSP). A pyramidal...
The pyramidal capacitated vehicle routing problem
Lysgaard, Jens
2010-01-01
This paper introduces the pyramidal capacitated vehicle routing problem (PCVRP) as a restricted version of the capacitated vehicle routing problem (CVRP). In the PCVRP each route is required to be pyramidal in a sense generalized from the pyramidal traveling salesman problem (PTSP). A pyramidal...
Fund allocation using capacitated vehicle routing problem
Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina
2014-09-01
In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.
Locating Depots for Capacitated Vehicle Routing
Goertz, Inge Li
2011-01-01
We study a location-routing problem in the context of capacitated vehicle routing. The input is a set of demand locations in a metric space and a fleet of k vehicles each of capacity Q. The objective is to locate k depots, one for each vehicle, and compute routes for the vehicles so that all demands are satisfied and the total cost is minimized. Our main result is a constant-factor approximation algorithm for this problem. To achieve this result, we reduce to the k-median-forest problem, which generalizes both k-median and minimum spanning tree, and which might be of independent interest. We give a (3+c)-approximation algorithm for k-median-forest, which leads to a (12+c)-approximation algorithm for the above location-routing problem, for any constant c>0. The algorithm for k-median-forest is just t-swap local search, and we prove that it has locality gap 3+2/t; this generalizes the corresponding result known for k-median. Finally we consider the "non-uniform" k-median-forest problem which has different cost ...
Capacitated Vehicle Routing with Non-Uniform Speeds
Gortz, Inge Li; Nagarajan, Viswanath; Ravi, R
2010-01-01
The capacitated vehicle routing problem (CVRP) involves distributing (identical) items from a depot to a set of demand locations, using a single capacitated vehicle. We study a generalization of this problem to the setting of multiple vehicles having non-uniform speeds (that we call Heterogenous CVRP), and present a constant-factor approximation algorithm. The technical heart of our result lies in achieving a constant approximation to the following TSP variant (called Heterogenous TSP). Given a metric denoting distances between vertices, a depot r containing k vehicles with possibly different speeds, the goal is to find a tour for each vehicle (starting and ending at r), so that every vertex is covered in some tour and the maximum completion time is minimized. This problem is precisely Heterogenous CVRP when vehicles are uncapacitated. The presence of non-uniform speeds introduces difficulties for employing standard tour-splitting techniques. In order to get a better understanding of this technique in our con...
A branch-and-cut-and-price algorithm for the cumulative capacitated vehicle routing problem
Wøhlk, Sanne; Lysgaard, Jens
2014-01-01
The paper considers the Cumulative Capacitated Vehicle Routing Problem (CCVRP), which is a variation of the well-known Capacitated Vehicle Routing Problem (CVRP). In this problem, the traditional objective of minimizing total distance or time traveled by the vehicles is replaced by minimizing the...
A branch-and-cut algorithm for the capacitated open vehicle routing problem
Letchford, A.N.; Lysgaard, Jens; Eglese, R.W.
2007-01-01
In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The algorithm is based on branch...... assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem....
A Branch-and-Cut Algorithm for the Capacitated Open Vehicle Routing Problem
Letchford, Adam N.; Lysgaard, Jens; Eglese, Richard W.
In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The algorithm is based on branch...... assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem....
Kui-Ting CHEN; Yijun Dai; Ke Fan; Takaaki Baba
2015-01-01
Capacitated vehicle routing problem with pickups and deliveries (CVRPPD) is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO) is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO) is proposed to solve th...
Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem
无
2006-01-01
Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid approximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimization (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
Optimization of Capacitated Vehicle Routing Problem by Nested Particle Swarm Optimization
Karuppusamy Kanthavel
2011-01-01
Full Text Available Problem statement: Vehicle routing problem determines the optimum route for each vehicle as a sequence of visiting cities. The problem has been defined as NP-hard and exact solution is relatively difficult to achieve for real time large scale models. Though several attempts to solve the problem were made in the literature, new approaches may be tried to solve the problem to further reduce computational efforts. Approach: In this context this study focuses on maximum utilization of loading capacity and determines the optimum set of vehicle routes for Capacitated Vehicle Routing Problem (CVRP by a Nested Particle Swarm Optimization (NPSO technique. The algorithm is implemented as Master PSO and slave PSO for the identification of candidate list and route sequence in nested form to optimize the model. Results: Benchmarking data set of capacitated vehicle routing is considered for the evaluations. The total distance of set vehicle route obtained by the new approach is compared with the best known solution and other existing techniques. Conclusions/Recommendations: The NPSO produces significant results and computational performance than the existing PSO algorithms. This newly proposed NPSO algorithm develops the vehicle schedule without any local optimization technique.
An Artificial Bee Colony Algorithm for the Capacitated Vehicle Routing Problem
Szeto, W.Y.; Wu, Yongzhong; Ho, Sin C.
This paper introduces an artificial bee colony heuristic for the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. The performance of the heuristic is evaluated on two sets of benchmark...... instances, and the computational results show that the heuristic produces good solutions....
Davendra, Donald; Zelinka, Ivan; Senkerik, Roman; Jasek, Roman; Bialic-Davendra, Magdalena
2012-11-01
One of the new emerging application strategies for optimization is the hybridization of existing metaheuristics. The research combines the unique paradigms of solution space sampling of SOMA and memory retention capabilities of Scatter Search for the task of capacitated vehicle routing problem. The new hybrid heuristic is tested on the Taillard sets and obtains good results.
A Food Chain Algorithm for Capacitated Vehicle Routing Problem with Recycling in Reverse Logistics
Song, Qiang; Gao, Xuexia; Santos, Emmanuel T.
2015-12-01
This paper introduces the capacitated vehicle routing problem with recycling in reverse logistics, and designs a food chain algorithm for it. Some illustrative examples are selected to conduct simulation and comparison. Numerical results show that the performance of the food chain algorithm is better than the genetic algorithm, particle swarm optimization as well as quantum evolutionary algorithm.
A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands
Christiansen, Christian Holk; Lysgaard, Jens
This article introduces a new exact algorithm for the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD). The CVRPSD can be formulated as a Set Partitioning Problem and it is shown that the associated column generation subproblem can be solved using a dynamic programming scheme....... Computational experiments show promising results....
A Centroid-based Heuristic Algorithm for the Capacitated Vehicle Routing Problem
Kwangcheol Shin; Sangyong Han
2012-01-01
The vehicle routing problem (VRP) is famous as a nondeterministic polynomial-time hard problem. This study proposes a centroid-based heuristic algorithm to solve the capacitated VRP in polynomial time. The proposed algorithm consists of three phases: cluster construction, cluster adjustment, and route establishment. At the cluster construction phase, the farthest node (customer) among un-clustered nodes is selected as a seed to form a cluster. The notion of the geometrical centre of a cluster...
Capacitated Vehicle Routing with Non-Uniform Speeds
Gørtz, Inge Li; Molinaro, Marco; Nagarajan, Viswanath;
2011-01-01
-uniform speeds (that we call Heterogenous CVRP), and present a constant-factor approximation algorithm. The technical heart of our result lies in achieving a constant approximation to the following TSP variant (called Heterogenous TSP). Given a metric denoting distances between vertices, a depot r containing k...... vehicles having speeds {λ i } i = 1 k , the goal is to find a tour for each vehicle (starting and ending at r), so that every vertex is covered in some tour and the maximum completion time is minimized. This problem is precisely Heterogenous CVRP when vehicles are uncapacitated. The presence of non......-uniform speeds introduces difficulties for employing standard tour-splitting techniques. In order to get a better understanding of this technique in our context, we appeal to ideas from the 2-approximation for minimum makespan scheduling in unrelated parallel machines of Lenstra et al. [19]. This motivates the...
An artificial bee colony algorithm for the capacitated vehicle routing problem
Szeto, W.Y.; Wu, Yongzhong; Ho, Sin C.
2011-01-01
This paper introduces an artificial bee colony heuristic for solving the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. An enhanced version of the artificial bee colony heuristic is also...... proposed to improve the solution quality of the original version. The performance of the enhanced heuristic is evaluated on two sets of standard benchmark instances, and compared with the original artificial bee colony heuristic. The computational results show that the enhanced heuristic outperforms the...... original one, and can produce good solutions when compared with the existing heuristics. These results seem to indicate that the enhanced heuristic is an alternative to solve the capacitated vehicle routing problem....
Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem
Fukasawa, R.; Longo, H.; Lysgaard, Jens; Poggi de Aragão, M.; Reis, M.; Uchoa, E.; Werneck, R.F.
2006-01-01
traditional Lagrangean relaxation over q-routes, the other defined by bound, degree and capacity constraints. This is equivalent to a linear program with exponentially many variables and constraints that can lead to lower bounds that are superior to those given by previous methods. The resulting branch......The best exact algorithms for the Capacitated Vehicle Routing Problem (CVRP) have been based on either branch-and-cut or Lagrangean relaxation/column generation. This paper presents an algorithm that combines both approaches: it works over the intersection of two polytopes, one associated with a...
Zheng Wang
2013-01-01
Full Text Available This paper presents a flexible solution methodology for the capacitated vehicle routing problem with stochastic travel times (CVRPSTT. One of the basic ideas of the methodology is to consider a vehicle working time lower than the actual maximum vehicle working time when designing CVRPSTT solutions. In this way, the working time surplus can be used to cope with unexpected congestions when necessary. Another important idea is to transform the CVRPSTT instance to a limited set of capacitated vehicle routing problems (CVRP, each of which is defined by a given percentage of the maximum vehicle working time. Thus, our approach can take advantage of any efficient heuristic that already exists for the CVRP. Based on the two key ideas, this paper presents a simulation-based algorithm, in which Monte Carlo simulation is used to obtain estimates of the cost and the reliability of each solution, and the Clarke and Wright heuristic is improved to generate more reliable solutions. Finally, a number of numerical experiments are done in the paper with the purpose of analyzing the efficiency of the described methodology under different uncertainty scenarios.
A branch-and-cut algorithm for the symmetric two-echelon capacitated vehicle routing problem
Jepsen, Mads Kehlet; Spoorendonk, Simon; Røpke, Stefan
2013-01-01
This paper presents an exact method for solving the symmetric two-echelon capacitated vehicle routing problem, a transportation problem concerned with the distribution of goods from a depot to a set of customers through a set of satellite locations. The presented method is based on an edge flow m...... model that is a relaxation and provides a valid lower bound. A specialized branching scheme is employed to obtain feasible solutions. Out of a test set of 93 instances the algorithm is able to solve 47 to optimality surpassing previous exact algorithms....
A Hybrid Bat Algorithm with Path Relinking for Capacitated Vehicle Routing Problem
Yongquan Zhou
2013-01-01
Full Text Available The capacitated vehicle routing problem (CVRP is an NP-hard problem with wide engineering and theoretical background. In this paper, a hybrid bat algorithm with path relinking (HBA-PR is proposed to solve CVRP. The HBA-PR is constructed based on the framework of continuous bat algorithm; the greedy randomized adaptive search procedure (GRASP and path relinking are effectively integrated into bat algorithm. Moreover, in order to further improve the performance, the random subsequences and single-point local search are operated with certain loudness (probability. In order to verify the validity of the method in this paper, and it's efficiency and with other existing methods, several classical CVRP instances from three classes of CVRP benchmarks are selected to tested. Experimental results and comparisons show that the HBA-PR is effective for CVRP.
Alberto Ochoa-Ortíz
2015-01-01
Full Text Available El problema de ruteo de vehículos bajo las limitaciones de capacidad y basado en computación ubicua desde una perspectiva relacionada con PSS (Producto-Servicio de Sistemas para desarrollar configuraciones para el transporte urbano de mercancías es abordado. Éste trabajo considera las especificidades de la logística urbana bajo un contexto de mercados emergentes. En este caso, involucra: i bajas competencias logísticas de los tomadores de decisiones; ii la limitada disponibilidad de datos; y iii restringido acceso a tecnología de alto desempeño para calcular rutas de transporte óptimas. Por lo tanto, se propone el uso de un software libre que proporciona soluciones de bajo costo (en tiempo y recursos. El artículo muestra la aplicación de los resultados de una herramienta de software basado en la Teoría de Grafos utilizado para analizar y resolver un CVRP (Capacitated Vehicle Routing Problem. Se utilizó el caso de una empresa local de distribución de alimentos situada en una gran ciudad de México. Sobre la base de una flora de vehículos pequeños, todos con las mismas especificaciones técnicas y una capacidad de carga comparable.
An optimization algorithm for a capacitated vehicle routing problem with time windows
PINAR KIRCI
2016-05-01
In this paper, vehicle routing problem (VRP) with time windows and real world constraints are considered as a real-world application on google maps. Also, tabu search is used and Hopfield neural networks is utilized. Basic constraints consist of customer demands, time windows, vehicle speed, vehicle capacity andworking hours. Recently, cost and on-time delivery are the most important actors in logistics. Thus, the logistic applications attract attention of companies. In logistic management, determining the locations of delivery points and deciding the path are the vital components that should be considered. Deciding the paths of vehicles provides companies to use their vehicles efficiently. And with utilizing optimized paths, big amounts of cost and time savings will be gained. The main aim of the work is providing the best path according to the needs of the customers, minimizing the costs with utilizing the VRP and presenting an application for companies that need logistic management. To compare the results, simulated annealing is used on special scenarios. And t-test is performed in the study for the visited path in km with p-value of 0.05.
Vehicle routing and the value of postponement
Pang, G.; L Muyldermans
2013-01-01
We study capacitated vehicle routing problems (CVRPs) in which the client demands occur over time and the collector or distributor performing the service can decide when to visit the clients. It has been reported in the literature that postponement of collection (or delivery) services may decrease the overall routing cost or distance. We investigate this issue in greater detail and report on experiments in different routing settings to uncover the impact of postponement on routing efficiency....
Capacitated arc routing problem and its extensions in waste collection
Fadzli, Mohammad; Najwa, Nurul [Institut Matematik Kejuruteraan, Universiti Malaysia Perlis, Kampus Pauh Putra, 02600 Arau, Perlis (Malaysia); Luis, Martino [Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)
2015-05-15
Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time.
Capacitated arc routing problem and its extensions in waste collection
Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles must start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time
An evolutionary algorithm for the capacitated arc routing problem.
Dalessandro Soares Vianna
2006-08-01
Full Text Available The Capacitated Arc Routing Problem (CARP consists of visiting a subset of edges of the graph that describes the problem. CARP applications include urban waste collection and inspection of power lines. The CARP is NP-hard, even in the single-vehicle case (called Rural Postman Problem. In this case, the use of metaheuristics is an efficient solution strategy. This paper proposes a hybrid genetic algorithm for the CARP, which is tested on available instances of the literature. The results obtained until now show the effectiveness of the proposed algorithm when it is compared with lower bounds described in the literature.
Optimal routing of electric vehicles
Andelmin, Juho
2014-01-01
In this thesis, a vehicle routing problem (VRP) variant tailored for plug-in battery electric vehicles (BEVs) is studied. The studied problem involves a fleet of identical BEVs located at a central depot, a set of customers that must be serviced within given time windows, and a set of charging stations where the vehicles can recharge their batteries. The objective is to design a set of vehicle routes, each starting and ending at the depot, so that each customer is serviced exactly once and th...
Stochastic vehicle routing with recourse
Gørtz, Inge Li; Nagarajan, Viswanath; Saket, Rishi
We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand...... instantiations, a recourse route is computed - but costs here become more expensive by a factor λ. We present an O(log2n ·log(nλ))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular...
Shortest Paths and Vehicle Routing
Petersen, Bjørn; Pisinger, David
2011-01-01
This thesis presents how to parallelize a shortest path labeling algorithm. It is shown how to handle Chvátal-Gomory rank-1 cuts in a column generation context. A Branch-and-Cut algorithm is given for the Elementary Shortest Paths Problem with Capacity Constraint. A reformulation of the Vehicle Routing Problem based on partial paths is presented. Finally, a practical application of finding shortest paths in the telecommunication industry is shown.
THE PERIODIC CAPACITATED ARC ROUTING PROBLEM LINEAR PROGRAMMING MODEL,METAHEURISTIC AND LOWER BOUNDS
Feng CHU; Nacima LABADI; Christian PRINS
2004-01-01
The Periodic Capacitated Arc Routing Problem (PCARP) generalizes the well known NP-hard Capacitated Arc Routing Problem (CARP) by extending the single period to multi-period horizon.The Capacitated Arc Routing Problem (CARP) is defined on an undirected network in which a fleet of identical vehicles is based at a depot node. A subset of edges, called tasks, must be serviced by a vehicle. The CARP consists of determining a set of feasible vehicle trips that minimizes the total cost of traversed edges. The PCARP involves the assignment of tasks to periods and the determination of vehicles trips in each period, to minimize the total cost on the whole horizon. This new problem arises in various real life applications such as waste collection, mail delivery, etc. In this paper, a new linear programming model and preliminary lower bounds based on graph transformation are proposed. A meta-heuristic approach - Scatter Search (SS) is developed for the PCARP and evaluated on a large variety of instances.
王超; 金淳; 韩庆平
2016-01-01
This paper proposed a multi-objective model for capacitated vehicle routing problem (CVRP)facing different target preference (MOCVRPFDTP)to solve CVRP more effectively and evaluate transportation cost comprehensively.There were three different preference structures in this model,which were joint optimization of loading and CVRP,absolute minimum vehi-cles preference,and path optimization preference.To solve this model,this paper constructed an algorithm framework with cor-responding algorithms.In experiments,the model and its solving methods display satisfactory performance in the testing for VR-PLIB,and they are more suitable for practical instance.%为了更有效地求解车辆路径问题、全方位地评估物流运输成本，提出了面向不同目标偏好的车载能力约束车辆路径问题的多目标优化模型（MOCVRPFDTP），其包括三种不同的偏好结构：装载与 CVRP 联合优化、绝对最小车辆数偏好及路径优化偏好。为了求解该模型，设计了算法架构及具体算法。在实验中，该模型及其求解方法对 CVRP 国际标准算例 VRPLIB 的测试结果显示了令人满意的性能，并且它更适用于实际 CVRP 问题的求解。
Classification of Dynamic Vehicle Routing Systems
Larsen, Allan; Madsen, Oli B.G.; Solomon, Marius M.
2007-01-01
classify dynamic vehicle routing systems. Methods for evaluation of the performance of algorithms that solve on-line routing problems are discussed and we list some of the most important issues to include in the system objective. Finally, we provide a three-echelon classification of dynamic vehicle routing...... systems based on their degree of dynamism and the system objective....
Vehicle routing problem in investment fund allocation
Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Mohd, Ismail
2013-04-01
Since its introduction by Dantzig and Ramser in 1959, vehicle routing problem keeps evolving in theories, applications and variability. The evolution in computing and technology are also important contributors to research in solving vehicle routing problem. The main sectors of interests among researchers and practitioners for vehicle routing problem are transportation, distribution and logistics. However, literature found that concept and benefits of vehicle routing problem are not taken advantages of by researchers in the field of investment. Other methods found used in investment include multi-objective programming, linear programming, goal programming and integer programming. Yet the application of vehicle routing problem is not fully explored. A proposal on a framework of the fund allocation optimization using vehicle routing problem is presented here. Preliminary results using FTSE Bursa Malaysia data testing the framework are also given.
A mathematical modeling proposal for a Multiple Tasks Periodic Capacitated Arc Routing Problem
Cleverson Gonçalves dos Santos
2015-12-01
Full Text Available The countless accidents and incidents occurred at dams at the last years, propelled the development of politics related with dams safety. One of the strategies is related to the plan for instrumentation and monitoring of dams. The monitoring demands from the technical team the reading of the auscultation data, in order to periodically monitor the dam. The monitoring plan of the dam can be modeled as a problem of mathematical program of the periodical capacitated arcs routing program (PCARP. The PCARP is considered as a generalization of the classic problem of routing in capacitated arcs (CARP due to two characteristics: 1 Planning period larger than a time unity, as that vehicle make several travels and; 2 frequency of associated visits to the arcs to be serviced over the planning horizon. For the dam's monitoring problem studied in this work, the frequent visits, along the time horizon, it is not associated to the arc, but to the instrument with which is intended to collect the data. Shows a new problem of Multiple tasks Periodic Capacitated Arc Routing Problem and its elaboration as an exact mathematical model. The new main characteristics presented are: multiple tasks to be performed on each edge or edges; different frequencies to accomplish each of the tasks; heterogeneous fleet; and flexibility for more than one vehicle passing through the same edge at the same day. The mathematical model was implemented and examples were generated randomly for the proposed model's validation.
Locating Depots for Capacitated Vehicle Routing
Gørtz, Inge Li; Nagarajan, Viswanath
2011-01-01
and parameter ρ ∈ R+, the goal in the k median forest problem is to find S ⊆ V with |S| = k minimizing: E u∈V d(u, S) + ρ · d(MST(V/S) ), where d(u, S) = minw∈S d(u,w) and MST(V/S) is a minimum spanning tree in the graph obtained by contracting S to a single vertex. We give a (3+E)-approximation algorithm for k...... forest problem when there is a different (unrelated) cost function c for the MST part, i.e. the objective is Eu∈V d(u, S) + c(MST(V/S) ). We show that the locality gap for this problem is unbounded even under multi-swaps, which contrasts with the c = d case. Nevertheless, we obtain a constant...
A Capacitated Location Routing Problem with Semi Soft Time Windows
Maryam Gharavani
2015-03-01
Full Text Available In this article we address The Location Routing Problem (LRP, where there is a set of customers with known demand and a set of potential depot site and there is a set of heterogeneous vehicle with a certain capacity. Due to the similarity of the problem with real world, the constraints of depot capacity and vehicle capacity as well as route length have been considered simultaneously. The model provided in this article is described concerning the semi soft time window in which that a delay in service delivery time results in delay costs. The total costs in the proposed model include, the total fixed costs of construction depot, fixed costs associated with the use of vehicles, the total distance traveled by the vehicles, the total time within the system for the vehicle and penalty cost associated with the violation of working hour of vehicles and penalty costs associated with delay time in the start of service to customers and the aim is to minimize the total cost. Due to its complexity, two Meta-Heuristic algorithms of Genetic and Tabu Search algorithm have been used. Since the performance of the Meta-Heuristic algorithms is significantly influenced by their parameters, Taguchi Method is used to set the parameters of developed algorithms. Finally, the result represents that the Genetic Algorithm and Tabu Search are significantly efficient in terms of better quality of solution and computational time respectively.
Stochastic vehicle routing: from theory to practice
Weyland, Dennis; Gambardella, Luca Maria; Montemanni, Roberto
2013-01-01
In this thesis we discuss practical and theoretical aspects of various stochastic vehicle routing problems. These are combinatorial optimization problems related to the field of transportation and logistics in which input data is (partially) represented in a stochastic way. More in detail, we focus on two-stage stochastic vehicle routing problems and in particular on so-called a priori optimization problems. The results are divided into a theoretical part and a practical part. In fact, the ...
Optimizing departure times in vehicle routes
Kok, A.L.; Hans, E.W.; Schutten, J.M.J.
2008-01-01
Most solution methods for the vehicle routing problem with time windows (VRPTW) develop routes from the earliest feasible departure time. However, in practice, temporal traffic congestions make that such solutions are not optimal with respect to minimizing the total duty time. Furthermore, VRPTW sol
Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics
Zuhaimy Ismail
2011-01-01
Full Text Available Problem statement: In this study, we introduced a new and real-life condition of Capacitated Arc Routing Problem (CARP, a model that represents vehicles operation in waste collection. In general, we studied the element of rain drops that affected the collected waste weight in total by imposed a new variable namely rainy weight age. In rainy days, the household refusals did not increase in volumes, but in weights due to rain drops. Consequently, this matter thus burdened vehicles capacity and prolonged its operation time. This dynamic variable thus changes the initial CARP model where the existing model did not consider other external elements that have effected onto the model. Approach: Then we developed and enhanced CARP by integrating stochastic demand and time windows to suit the models with our specific case. Results: Objectively, CARP with stochastic demand (CARPSD and CARP with time windows (CARPTW were designed to minimize the total routing cost and number of trips for a vehicle. Our approach is to design CARP models in almost likely to road layout in residential area and graphically this model is called mesh network. We also developed a constructive heuristic that is called nearest procedure based on highest demand/cost (NPHDC and work in conjunction with switching rules to search the feasible solution. Conclusion: Our preliminary results show a higher cost and more trips are needed when the vehicle operates in rainy day compared to normal day operation.
Genetic algorithms for the vehicle routing problem
Volna, Eva
2016-06-01
The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization tasks. This problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. Evolutionary algorithms are general iterative algorithms for combinatorial optimization. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. This problem is known to be NP-hard; hence many heuristic procedures for its solution have been suggested. For such problems it is often desirable to obtain approximate solutions, so they can be found fast enough and are sufficiently accurate for the purpose. In this paper we have performed an experimental study that indicates the suitable use of genetic algorithms for the vehicle routing problem.
Rich Vehicle Routing Problems and Applications
Wen, Min
given set of customers. The VRP is a computationally hard combinatorial problem and has been intensively studied by numerous researchers in the last fifty years. Due to the significant economic benefit that can be achieved by optimizing the routing problems in practice, more and more attention has been......The Vehicle Routing Problem (VRP) is one of the most important and challenging optimization problems in the field of Operations Research. It was introduced by Dantzig and Ramser (1959) and defined as the problem of designing the optimal set of routes for a fleet of vehicles in order to serve a...... problems in the sense that consolidation decisions have to be made at the depot and these decisions interact with the planning of pickup and delivery routes. We presented a mathematical model and proposed a Tabu Search based heuristic to solve it. It is shown that the approach can produce near-optimal...
Measurement of vehicle-load using capacitance and acceleration transducers
Over-loading is a common problem in some developing countries. Currently, large and fixed measurement systems are used to measure the load of vehicles travelling on highways. This paper presents an on-vehicle measuring device, which is based on measurement of change in capacitance due to variation in distance between electrodes mounted on vehicles. The on-vehicle leaf springs are used as a key part of the weighing transducer. Acceleration transducers are used to measure the vehicle's forward and the vertical accelerations. A feature of this on-vehicle measuring device is that it can provide both static and dynamic load measurements. The drivers can check the load in the cab, and the highway inspectors can check the load at any time and any place through radio communication, thus identifying over-loaded vehicles
Combining Nearest Neighbor Search with Tabu Search for Large-Scale Vehicle Routing Problem
Du, Lingling; He, Ruhan
The vehicle routing problem is a classical problem in operations research, where the objective is to design least cost routes for a fleet of identical capacitated vehicles to service geographically scattered customers. In this paper, we present a new and effective hybrid metaheuristic algorithm for large-scale vehicle routing problem. The algorithm combines the strengths of the well-known Nearest Neighbor Search and Tabu Search into a two-stage procedure. More precisely, Nearest Neighbor Search is used to construct initial routes in the first stage and the Tabu Search is utilized to optimize the intra-route and the inter-route in the second stage. The presented algorithm is specifically designed for large-scale problems. The computational experiments were carried out on a standard benchmark and a real dataset with 6772 tobacco customers. The results demonstrate that the suggested method is highly competitive.
Vehicle Routing and the Value of Postponement
Asim, Muhammad
2008-01-01
Industrial wisdom presumes that postponing the collection (or delivery) services reduces the transportation cost & most of the studies conducted in practical scenarios also substantiate this belief. However there is a dearth of in-depth research assessing the value of postponement in vehicle routing context. This research aims to explore the significance of postponement & its inter-relationship with related problem parameters such as vehicle capacity, clients' density, location of clients & d...
The Vehicle Routing Problem with Limited Vehicle Capacities
Fernando Taracena Sanz
2013-09-01
Full Text Available The vehicle routing problem (VRP has been an important research topic during the last decades because of his vital role in the productive systems efficiency. Most of the work done in this area has been directed to solve large scale problems which may not apply for small companies which are a very important engine of the world economy. This paper approaches the problem when limited vehicle resources are present and road transportation is used. This study assumes variable customer orders. Variable volume and weight vehicle capacities are considered and the proposed algorithm develops the vehicle delivery routes and the set of customer orders to deliver per vehicle minimizing a cost objective function. In sampling small company’s logistics costs, big cost savings are found when using the proposed method.
A global repair operator for capacitated arc routing problem.
Mei, Yi; Tang, Ke; Yao, Xin
2009-06-01
Capacitated arc routing problem (CARP) has attracted much attention during the last few years due to its wide applications in real life. Since CARP is NP-hard and exact methods are only applicable for small instances, heuristics and metaheuristic methods are widely adopted when solving CARP. This paper demonstrates one major disadvantage encountered by traditional search algorithms and proposes a novel operator named global repair operator (GRO) to address it. We further embed GRO in a recently proposed tabu search algorithm (TSA) and apply the resultant repair-based tabu search (RTS) algorithm to five well-known benchmark test sets. Empirical results suggest that RTS not only outperforms TSA in terms of quality of solutions but also converges to the solutions faster. Moreover, RTS is also competitive with a number of state-of-the-art approaches for CARP. The efficacy of GRO is thereby justified. More importantly, since GRO is not specifically designed for the referred TSA, it might be a potential tool for improving any existing method that adopts the same solution representation. PMID:19211356
Vehicle Coordinated Strategy for Vehicle Routing Problem with Fuzzy Demands
Chang-shi Liu
2016-01-01
Full Text Available The vehicle routing problem with fuzzy demands (VRPFD is considered. A fuzzy reasoning constrained program model is formulated for VRPFD, and a hybrid ant colony algorithm is proposed to minimize total travel distance. Specifically, the two-vehicle-paired loop coordinated strategy is presented to reduce the additional distance, unloading times, and waste capacity caused by the service failure due to the uncertain demands. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed approaches.
Zhang, Rick; Rossi, Federico; Pavone, Marco
2016-01-01
This paper considers the problem of routing and rebalancing a shared fleet of autonomous (i.e., self-driving) vehicles providing on-demand mobility within a capacitated transportation network, where congestion might disrupt throughput. We model the problem within a network flow framework and show that under relatively mild assumptions the rebalancing vehicles, if properly coordinated, do not lead to an increase in congestion (in stark contrast to common belief). From an algorithmic standpoint...
Vehicle routing with cross-docking
Wen, Min; Larsen, Jesper; Clausen, Jens; Cordeau, Jean-Francois; Laporte, Gilbert
2009-01-01
Over the past decade, cross-docking has emerged as an important material handling technology in transportation. A variation of the well-known Vehicle Routing Problem (VRP), the VRP with Cross-Docking (VRPCD) arises in a number of logistics planning contexts. This paper addresses the VRPCD, where a...... set of homogeneous vehicles are used to transport orders from the suppliers to the corresponding customers via a cross-dock. The orders can be consolidated at the cross-dock but cannot be stored for very long because the cross-dock does not have long-term inventory-holding capabilities. The objective...
Vehicle routing problem for save fuel consumption
LIU Hao; AI Wen-wen
2016-01-01
This study has extended a vehicle routing problem,by considering economy of fuel,and constructing a LF-VRP model,to obtain optimal fixed costs.Our objective was to minimize not only distance,but also the fuel consumption.A example were developed to solve the proposed models.It was found that our proposed models yielded better results than the traditional VRP models.
Application of Harmony Search to Vehicle Routing
Zong W. Geem
2005-01-01
Full Text Available A phenomenon-inspired meta-heuristic algorithm, harmony search, imitating music improvisation process, is introduced and applied to vehicle routing problem, then compared with one of the popular evolutionary algorithms, genetic algorithm. The harmony search algorithm conceptualized a group of musicians together trying to search for better state of harmony. This algorithm was applied to a test traffic network composed of one bus depot, one school and ten bus stops with demand by commuting students. This school bus routing example is a multi-objective problem to minimize both the number of operating buses and the total travel time of all buses while satisfying bus capacity and time window constraints. Harmony search could find good solution within the reasonable amount of time and computation.
Metaheuristics applied to vehicle routing. A case study. Part 3: Genetic Clustering and Tabu Routing
Guillermo González Vargas
2010-04-01
Full Text Available This paper presents hybrid meta-heuristics called Genetic Clustering and Tabu Routing for solving a vehicle routing problem using two phases methodology: first clustering and then routing. The results are compared with those obtained using meta-heuristics and heuristic techniques presented in previous papers. Genetic clustering and Tabu routing average results were 23% and 9.1% better, respectively.
A Branch-and-Price Algorithm for the Capacitated Arc Routing Problem with Stochastic Demands
Christiansen, Christian Holk; Lysgaard, Jens; Wøhlk, Sanne
2009-01-01
We address the Capacitated Arc Routing Problem with Stochastic Demands (CARPSD), which we formulate as a Set Partitioning Problem. The CARPSD is solved by a Branch-and-Price algorithm, which we apply without graph transformation. The demand's stochastic nature is incorporated into the pricing pro...... problem. Computational results are reported....
Vehicle Routing With User Generated Trajectory Data
Ceikute, Vaida; Jensen, Christian S.
shortest nor fastest, indicating that drivers value route properties that are diverse and hard to quantify or even identify. We propose a routing service that uses an existing routing service while exploiting the availability of historical route usage data from local drivers. Given a source and destination......, the service recommends a corresponding route that is most preferred by local drivers. It uses a route preference function that takes into account the number of distinct drivers and the number of trips associated with a route, as well as temporal aspects of the trips. The paper provides empirical...... studies with real route usage data and an existing online routing service....
Flexible Bond Wire Capacitive Strain Sensor for Vehicle Tyres.
Cao, Siyang; Pyatt, Simon; Anthony, Carl J; Kubba, Ammar I; Kubba, Ali E; Olatunbosun, Oluremi
2016-01-01
The safety of the driving experience and manoeuvrability of a vehicle can be improved by detecting the strain in tyres. To measure strain accurately in rubber, the strain sensor needs to be flexible so that it does not deform the medium that it is measuring. In this work, a novel flexible bond wire capacitive strain sensor for measuring the strain in tyres is developed, fabricated and calibrated. An array of 25 micron diameter wire bonds in an approximately 8 mm × 8 mm area is built to create an interdigitated structure, which consists of 50 wire loops resulting in 49 capacitor pairs in parallel. Laser machining was used to pattern copper on a flexible printed circuit board PCB to make the bond pads for the wire attachment. The wire array was finally packaged and embedded in polydimethylsiloxane (PDMS), which acts as the structural material that is strained. The capacitance of the device is in a linear like relationship with respect to the strain, which can measure the strain up to at least ±60,000 micro-strain (±6%) with a resolution of ~132 micro-strain (0.013%). In-tyre testing under static loading has shown the ability of the sensor to measure large tyre strains. The technology used for sensor fabrication lends itself to mass production and so the design is considered to be consistent with low cost commercialisable strain sensing technology. PMID:27338402
Pop Petrica
2011-01-01
Full Text Available Classical combinatorial optimization problems can be generalized in a natural way by considering a related problem relative to a given partition of the nodes of the graph into node sets. In the literature one can find generalized problems such as: generalized minimum spanning tree, generalized traveling salesman problem, generalized Steiner tree problem, generalized vehicle routing problem, etc. These generalized problems typically belong to the class of NP-complete problems; they are harder than the classical ones, and nowadays are intensively studied due to their interesting properties and applications in the real world. Because of the complexity of finding the optimal or near-optimal solution in case of the generalized combinatorial optimization problems, great effort has been made, by many researchers, to develop efficient ways of their transformation into classical corresponding variants. We present in this paper an efficient way of transforming the generalized vehicle routing problem into the vehicle routing problem, and a new integer programming formulation of the problem.
Optimization of Multiple Vehicle Routing Problems using Approximation Algorithms
Nallusamy, R; K. Duraiswamy,; Dhanalaksmi, R.; P. Parthiban
2010-01-01
This paper deals with generating of an optimized route for multiple Vehicle routing Problems (mVRP). We used a methodology of clustering the given cities depending upon the number of vehicles and each cluster is allotted to a vehicle. k- Means clustering algorithm has been used for easy clustering of the cities. In this way the mVRP has been converted into VRP which is simple in computation compared to mVRP. After clustering, an optimized route is generated for each vehicle in its allotted cl...
Distributed Decision Making in Combined Vehicle Routing and Break Scheduling
Meyer, Christoph Manuel; Kopfer, Herbert; Kok, Adrianus Leendert; Schutten, Marco
2009-01-01
The problem of combined vehicle routing and break scheduling comprises three subproblems: clustering of customer requests, routing of vehicles, and break scheduling. In practice, these subproblems are usually solved in the interaction between planners and drivers. We consider the case that the planner performs the clustering and the drivers perform the routing and break scheduling. To analyze this problem, we embed it into the framework of distributed decision making proposed by Schneeweiss (...
Route Elimination Heuristic for Vehicle Routing Problem with Time Windows
Sándor Csiszár
2005-11-01
Full Text Available The paper deals with the design of a route elimination (RE algorithm for thevehicle routing problem with time windows (VRPTW. The problem has two objectives, oneof them is the minimal number of routes the other is the minimal cost. To cope with theseobjectives effectively two-phase solutions are often suggested in the relevant literature. Inthe first phase the main focus is the route elimination, in the second one it is the costreduction. The algorithm described here is a part of a complete VRPWT study. The methodwas developed by studying the graph behaviour during the route elimination. For thispurpose a model -called “Magic Bricks” was developed. The computation results on theSolomon problem set show that the developed algorithm is competitive with the best ones.
Speed-Consumption Tradeoff for Electric Vehicle Route Planning
Baum, Moritz; Dibbelt, Julian; Hübschle-Schneider, Lorenz; Pajor, Thomas; Wagner, Dorothea
2014-01-01
We study the problem of computing routes for electric vehicles (EVs) in road networks. Since their battery capacity is limited, and consumed energy per distance increases with velocity, driving the fastest route is often not desirable and may even be infeasible. On the other hand, the energy-optimal route may be too conservative in that it contains unnecessary detours or simply takes too long. In this work, we propose to use multicriteria optimization to obtain Pareto sets of routes that trad...
The price of commitment in online stochastic vehicle routing
Bent, Russell W [Los Alamos National Laboratory; Van Hentenryck, Pascal [BROWN UNIV
2009-01-01
This paper considers online stochastic multiple vehicle routing with time windows in which requests arrive dynamically and the goal is to maximize the number of serviced customers. Early work has focused on very flexible routing settings where the decision to assign a vehicle to a customer is delayed until a vehicle is actually deployed to the customer. Motivated by real applications that require stability in the decision making, this paper considers a setting where the decision to assign a customer request to a vehicle must be taken when that request is accepted. Experimental results suggest that this constraint severely degrades the performance of existing algorithms. However, the paper shows how the use of stochastic information for vehicle assignment and request acceptance improves decision quality considerably. Moreover, the use of resource augmentation quantifies precisely the cost of commitment in online vehicle routing.
Optimizing investment fund allocation using vehicle routing problem framework
Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita
2014-07-01
The objective of investment is to maximize total returns or minimize total risks. To determine the optimum order of investment, vehicle routing problem method is used. The method which is widely used in the field of resource distribution shares almost similar characteristics with the problem of investment fund allocation. In this paper we describe and elucidate the concept of using vehicle routing problem framework in optimizing the allocation of investment fund. To better illustrate these similarities, sectorial data from FTSE Bursa Malaysia is used. Results show that different values of utility for risk-averse investors generate the same investment routes.
Routing of Electric Vehicles: City Distribution in Copenhagen
Linde, Esben; Larsen, Allan; Nørrelund, Anders Vedsted;
. The objective is to find the least cost plan for EV routing and compare this to conventional routing. A heuristic method is developed and tested on data based on real-life collected data on distribution vehicles in central Copenhagen, Denmark. The EVRPTW has so far received little attention in the literature......In this work, a Vehicle Routing Problem with Time Windows considering EV constraints of limited driving range and freight capacity is addressed (EVRPTW). The EVs are allowed to recharge at certain locations, and aspects of intelligent location of these recharging points are considered...
A Study of Urgency Vehicle Routing Disruption Management Problem
Xuping Wang
2010-12-01
Full Text Available If a transit vehicle breaks down on a schedule trip, there are some vehicles in the system need to serve this trip and the former plan must be changed. For solving the urgency vehicle routing problem with disruption that may be vehicle breakdowns or traffic accidents in the logistics distribution system, through the analysis of the problem and the disruption measurement, the mathematics model is given based on the thought of disruption management. For the characteristics of the problem, a Lagrangian relaxation is given to simplify the model, and decompose the problem into two parts. The Lagrangian multiplier is given by subgradient method and the subproblems are solved by saving approach to gain the initial solution. A fast insertion algorithm is given to obtain a feasible solution for the primal problem. The results show that the algorithm designed in this paper performs very well for solving the urgency vehicle routing disruption management problem.
Optimization of Multiple Vehicle Routing Problems Using Approximation Algorithms
R. Nallusamy
2009-12-01
Full Text Available This paper deals with generating of an optimized route for multiple Vehicle routing Problems (mVRP. We used a methodology of clustering the given cities depending upon the number of vehicles and eachcluster is allotted to a vehicle. k- Means clustering algorithm has been used for easy clustering of the cities. In this way the mVRP has been converted into VRP which is simple in computation compared to mVRP. After clustering, an optimized route is generated for each vehicle in its allotted cluster. Once the clustering had been done and after the cities were allocated to the various vehicles, each cluster/tour was taken as an individual Vehicle Routing problem and the steps of Genetic Algorithm were applied to the cluster and iterated to obtain the most optimal value of the distance after convergence takes place. After the application of the variousheuristic techniques, it was found that the Genetic algorithm gave a better result and a more optimal tour for mVRPs in short computational time than other Algorithms due to the extensive search and constructive nature of the algorithm.
A Subpath Ejection Method for the Vehicle Routing Problem
César Rego
1998-01-01
Generically, ejection chains are methods conceived to allow solution transformations to be efficiently carried out by modifying a variable number of their components at each step of a local search algorithm. We consider a subpath ejection chain method for the vehicle routing problem (VRP) under capacity and route length restrictions. The method undertakes the identification of a substructure named the flower reference structure which, besides coordinating moves during an ejection chain constr...
Parallelization of the Vehicle Routing Problem with Time Windows
Larsen, Jesper
1999-01-01
This dissertation presents a number of algorithms for solving the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP). In the VRP a fleet of vehicles based at a central depot must service a set of...... customers. In the VRPTW each customer has a time window. Service of a customer must begin within the interval given by the time window. The objective is to minimize some aspect of operating costs (e.g. total distance traveled, number of vehicles needed or a combination of parameters). Since the late 80's...... also been obtained using Lagrange relaxation. This dissertation is divided into three parts. First the theoretical framework is described. Thereafter a number of techniques to improve the performance of the column-generation framework are proposed and analyzed. Finally a parallel algorithm based on the...
The vehicle routing problem with edge set costs
Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David
2011-01-01
We consider an important generalization of the vehicle routing problem with time windows in which a fixed cost must be paid for accessing a set of edges. This fixed cost could reflect payment for toll roads, investment in new facilities, the need for certifications and other costly investments. The certifications and contributions impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. Different versions for defining the e...
The selective vehicle routing problem in a collaborative environment
DEFRYN, Christof; Sörensen, Kenneth; CORNELISSENS, Trijntje
2015-01-01
We consider a selective vehicle routing problem, in which customers belonging to different partners in a logistic coalition are served in a single logistic operation with multiple vehicles. Each partner determines a cost of non-delivery (CND) for each of its customers, and a central algorithm creates an operational plan, including the decision on which customers to serve and in which trip. The total transportation cost of the coalition is then divided back to the partners through a cost alloc...
Heuristics for Routing Heterogeneous Unmanned Vehicles with Fuel Constraints
David Levy
2014-01-01
Full Text Available This paper addresses a multiple depot, multiple unmanned vehicle routing problem with fuel constraints. The objective of the problem is to find a tour for each vehicle such that all the specified targets are visited at least once by some vehicle, the tours satisfy the fuel constraints, and the total travel cost of the vehicles is a minimum. We consider a scenario where the vehicles are allowed to refuel by visiting any of the depots or fuel stations. This is a difficult optimization problem that involves partitioning the targets among the vehicles and finding a feasible tour for each vehicle. The focus of this paper is on developing fast variable neighborhood descent (VND and variable neighborhood search (VNS heuristics for finding good feasible solutions for large instances of the vehicle routing problem. Simulation results are presented to corroborate the performance of the proposed heuristics on a set of 23 large instances obtained from a standard library. These results show that the proposed VND heuristic, on an average, performed better than the proposed VNS heuristic for the tested instances.
Route-Based Control of Hybrid Electric Vehicles: Preprint
Gonder, J. D.
2008-01-01
Today's hybrid electric vehicle controls cannot always provide maximum fuel savings over all drive cycles. Route-based controls could improve HEV fuel efficiency by 2%-4% and help save nearly 6.5 million gallons of fuel annually.
A heuristic algorithm for a multi-product four-layer capacitated location-routing problem
Mohsen Hamidi
2014-01-01
Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.
ACTIVITY-BASED COSTING FOR VEHICLE ROUTING PROBLEMS
A. J. Moolman
2012-01-01
Full Text Available
ENGLISH ABSTRACT:Activity-based costing (ABC is a costing model that identifies activity costs in an organisation. It assigns the cost of activity resources to generate the actual cost of products in order to eliminateunprofitable products and to lowerthe prices of overpriced ones. The vehicle routing problem (VRP is a combinatorial optimisation and nonlinear programming problem that seeks to service a number of customers with a fleet of vehicles in a cost-effective manner. In this article we propose a new approach to determine costing for vehicle routing type problems. The methodology incorporates the predictive sharing of a resource by clustering producers.
AFRIKAANSE OPSOMMING: ‘Activity-based costing’ (ABC is ’n kostemodel wat die aktiwiteitskoste in ’n organisasie identifiseer. Dit allokeer die koste van die bronne sodat die ware koste van die vervaardiging en dienste van die produk bereken kan word om winsgewendheid te bepaal. Die ‘vehicle routing problem’ (VRP is ’n kombinatoriese optimisering en nie-lineêre programmeringsprobleem wat verskeie kliënte met ’n vloot voertuie in die mees koste- effektiewe manier bedien. Die artikel bespreek ’n nuwe metode om die kombinasie van probleme op te los. Die metode maak gebruik van groeperingsalgoritmes om meer akkurate voertuig deling te voorspel.
Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem
Annisa Kesy Garside
2014-01-01
Full Text Available Genetic Algorithm, Tabu Search, Simulated Annealing, and Ant Colony Optimization showed a good performance in solving vehicle routing problem. However, the generated solution of those algorithms was changeable regarding on the input parameter of each algorithm. CODEQ is a new, parameter free meta-heuristic algorithm that had been successfully used to solve constrained optimization problems, integer programming, and feed-forward neural network. The purpose of this research are improving CODEQ algorithm to solve vehicle routing problem and testing the performance of the improved algorithm. CODEQ algorithm is started with population initiation as initial solution, generated of mutant vector for each parent in every iteration, replacement of parent by mutant when fitness function value of mutant is better than parent’s, generated of new vector for each iteration based on opposition value or chaos principle, replacement of worst solution by new vector when fitness function value of new vector is better, iteration ceasing when stooping criterion is achieved, and sub-tour determination based on vehicle capacity constraint. The result showed that the average deviation of the best-known and the best-test value is 6.35%. Therefore, CODEQ algorithm is good in solving vehicle routing problem.
Solving the time dependent vehicle routing problem by metaheuristic algorithms
Johar, Farhana; Potts, Chris; Bennell, Julia
2015-02-01
The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer location. This implies an efficient synchronization of production and distribution activities. Hence, this study will look into the routing of vehicles which departs from the depot at varies time due to the variation in manufacturing process. We consider a single production line where demanded products are being process one at a time once orders have been received from the customers. It is assumed that order released from the production line will be loaded into scheduled vehicle which ready to be delivered. However, the delivery could only be done once all orders scheduled in the vehicle have been released from the production line. Therefore, there could be lateness on the delivery process from awaiting all customers' order of the route to be released. Our objective is to determine a schedule for vehicle routing that minimizes the solution cost including the travelling and tardiness cost. A mathematical formulation is developed to represent the problem and will be solved by two metaheuristics; Variable Neighborhood Search (VNS) and Tabu Search (TS). These algorithms will be coded in C ++ programming and run using 56's Solomon instances with some modification. The outcome of this experiment can be interpreted as the quality criteria of the different approximation methods. The comparison done shown that VNS gave the better results while consuming reasonable computational efforts.
The vehicle routing problem with edge set costs
Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David
We consider an important generalization of the vehicle routing problem with time windows in which a fixed cost must be paid for accessing a set of edges. This fixed cost could reflect payment for toll roads, investment in new facilities, the need for certifications and other costly investments. The...... certifications and contributions impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. Different versions for defining the edge sets are discussed and formulated. A MIP-formulation of the problem is presented, and a solution method based on...
Vehicle routing problem with time-varying speed
LIU Yun-zhong
2010-01-01
Vehicle routing problem with time-varying speed(VRPTS)is a generalization of vehicle routing problem in which the travel speed between two locations depends on the passing areas and the time of a day.This paper proposes a simple model for estimating time-varying travel speeds in VRPTS that relieves much bur den to the data-related problems.The study further presents three heuristics(saving technique,proximity priority searching technique,and insertion technique)for VRPTS,developed by extending and modifying the existing heuristics for conventional VRP.The results of computational experiments demonstrate that the proposed estimation model performs well and the saving technique is the best among the three heuristics.
The vehicle routing problem with time windows and temporal dependencies
Dohn, Anders Høeg; Rasmussen, Matias Sevel; Larsen, Jesper
2011-01-01
In this article, we formulate the vehicle routing problem with time windows and temporal dependencies. The problem is an extension of the well studied vehicle routing problem with time windows. In addition to the usual constraints, a scheduled time of one visit may restrain the scheduling options...... on the relaxed master problems. Finally, a computational study is performed to quantitatively reveal strengths and weaknesses of the proposed formulations. It is concluded that, depending on the problem at hand, the best performance is achieved either by relaxing the generalized precedence constraints...... in the master problem, or by using a time‐indexed model, where generalized precedence constraints are added as cuts when they become severely violated. © 2011 Wiley Periodicals, Inc. NETWORKS, Vol. 58(4), 273–289 2011...
A green vehicle routing problem with customer satisfaction criteria
Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.
2016-08-01
This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.
STUDI TENTANG TRAVELLING SALESMAN DAN VEHICLE ROUTING PROBLEM DENGAN TIME WINDOWS
I Nyoman Sutapa
2003-01-01
Full Text Available The article shows the study of model development of travelling salesman problem. Three models are studied, i.e. travelling salesman problem with time windows, vehicle routing problem, and vehicle routing problem with time windows. Abstract in Bahasa Indonesia : Dalam artikel ini dipaparkan kajian mengenai pengembangan model travelling salesman problem. Ada tiga model yang dikaji yaitu travelling salesman problem dengan time windows, vehicle routing problem, serta vehicle routing problem dengan time windows. Kata-kunci: travelling salesman problem, vehicle routing problem, time windows.
Dynamic vehicle routing problems: Three decades and counting
Psaraftis, Harilaos N.; Wen, Min; Kontovas, Christos A.
2016-01-01
of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the......Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy...... nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit...
A Survey on Routing Mechanism and Techniques in Vehicle to Vehicle Communication (VANET
Yugal Kumar
2011-02-01
Full Text Available Now a day, one of the most attractive research topics in the area of Intelligent Traffic Control is Intervehiclecommunication. In V2V communication or we can also called VANET i.e. vehicular ad-hocnetwork; a vehicle can communicate to its neighboring vehicles even in the absence of a central BaseStation. The concept of this direct communication is to send vehicle safety messages one-to-one or oneto-many vehicles via wireless connection. Such messages are usually short in length and have very shortlifetime in which they must reach at the destination. The Inter-vehicle communication system is an adhocnetwork with high mobility and changing number of nodes, where mobile nodes dynamically createtemporary networks and transferring messages from one node to others by using multiple hops due tolimitation of short range. The routing in vehicular Ad hoc Networks (VANET has attracted manyattentions during the last few years. So in this paper we are focusing on the routing concept for theVANET i.e. principles for routing, decomposition of the routing function and requirement. The datadelivery through Vehicular Ad-hoc Networks is challenging since it must efficiently handle rapidtopology changes and a fragmented network.
Intelligent emission-sensitive routing for plugin hybrid electric vehicles.
Sun, Zhonghao; Zhou, Xingshe
2016-01-01
The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs. PMID:27026933
Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system
Liu, Mianfang; Xiong, Shengwu; Li, Bixiang
2016-05-01
With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.
SOLVING THE PROBLEM OF VEHICLE ROUTING BY EVOLUTIONARY ALGORITHM
Remigiusz Romuald Iwańkowicz
2016-03-01
Full Text Available In the presented work the vehicle routing problem is formulated, which concerns planning the collection of wastes by one garbage truck from a certain number of collection points. The garbage truck begins its route in the base point, collects the load in subsequent collection points, then drives the wastes to the disposal site (landfill or sorting plant and returns to the another visited collection points. The filled garbage truck each time goes to the disposal site. It returns to the base after driving wastes from all collection points. Optimization model is based on genetic algorithm where individual is the whole garbage collection plan. Permutation is proposed as the code of the individual.
On the vehicle routing problem with time windows
Kallehauge, Brian; Madsen, Oli B.G.; Larsen, Jesper; Madsen, Kaj
2006-01-01
Den danske titel på denne afhandling er ‘Ruteplanlægningsproblemet med tidsvinduer’. Dette problem omhandler den optimale styring af en flåde af lastbiler mellem et lager og et antal kunder, der skal besøges inden for et bestemt tidsinterval, et såkaldt tidsvindue. Formålet med denne afhandling er udvikling af nye og effektive metoder til løsning af ruteplanlægningsproblemet med tidsvinduer (vehicle routing problem with time windows - VRPTW). Afhandlingen består af et afsnit af introducerende...
Cooperative vehicle routing problem: an opportunity for cost saving
Zibaei, Sedighe; Hafezalkotob, Ashkan; Ghashami, Seyed Sajad
2016-02-01
In this paper, a novel methodology is proposed to solve a cooperative multi-depot vehicle routing problem. We establish a mathematical model for multi-owner VRP in which each owner (i.e. player) manages single or multiple depots. The basic idea consists of offering an option that owners cooperatively manage the VRP to save their costs. We present cooperative game theory techniques for cost saving allocations which are obtained from various coalitions of owners. The methodology is illustrated with a numerical example in which different coalitions of the players are evaluated along with the results of cooperation and cost saving allocation methods.
International Workshop on Vehicle Routing in Practice (VIP’08) - Oppsummering
Hasle, Geir
2008-01-01
Den internasjonale konferansen Vehicle Routing in Practice 2008 (VIP’08) ble gjennomført på en meget vellykket måte 12.-14. juni 2008 på Soria Moria konferansehotell i Oslo. Workshopen hadde 28 deltakere, hvorav 15 meget anerkjente forskere fra utlandet og 13 fra de tre norske VRP-forskningsgruppene ved NTNU, Høgskolen i Molde og SINTEF. VIP’08 samlet erfarne forskere fra utlandet og Norge samt norske PhD og postdoktorstipendiater. Det var 25 foredrag inndelt i 8 sesjoner etter fagtema (en st...
Reachability cuts for the vehicle routing problem with time windows
Lysgaard, Jens
2004-01-01
This paper introduces a class of cuts, called reachability cuts, for the Vehicle Routing Problem with Time Windows (VRPTW). Reachability cuts are closely related to cuts derived from precedence constraints in the Asymmetric Traveling Salesman Problem with Time Windows and to k-path cuts for the...... VRPTW. In particular, any reachability cut dominates one or more k-path cuts. The paper presents separation procedures for reachability cuts and reports computational experiments on well-known VRPTW instances. The computational results suggest that reachability cuts can be highly useful as cutting...
Vehicle routing for the last mile of power system restoration
Bent, Russell W [Los Alamos National Laboratory; Coffrin, Carleton [Los Alamos National Laboratory; Van Hentenryck, Pascal [BROWN UNIV.
2010-11-23
This paper studied a novel problem in power system restoration: the Power Restoration Vehicle Routing Problem (PRVRP). The goal of PRVRPs is to decide how coordinate repair crews effectively in order to recover from blackouts as fast as possible after a disaster has occurred. PRVRPs are complex problems that combine vehicle routing and power restoration scheduling problems. The paper proposed a multi-stage optimization algorithm based on the idea of constraint injection that meets the aggressive runtime constraints necessary for disaster recovery. The algorithms were validated on benchmarks produced by the Los Alamos National Laboratory, using the infrastructure of the United States. The disaster scenarios were generated by state-of-the-art hurricane simulation tools similar to those used by the National Hurricane Center. Experimental results show that the constraint-injection algorithms can reduce the blackouts by 50% or more over field practices. Moreover, the results show that the constraint-injection algorithm using large neighborhood search over a blackbox simulator provide competitive quality and scales better than using a MIP solver on the subproblems.
Analysis of the single-vehicle cyclic inventory routing problem
Aghezzaf, El-Houssaine; Zhong, Yiqing; Raa, Birger; Mateo, Manel
2012-11-01
The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of a repetitive distribution of a product from a single depot to a selected subset of customers. For each customer, selected for replenishments, the supplier collects a corresponding fixed reward. The objective is to determine the subset of customers to replenish, the quantity of the product to be delivered to each and to design the vehicle route so that the resulting profit (difference between the total reward and the total logistical cost) is maximised while preventing stockouts at each of the selected customers. This problem appears often as a sub-problem in many logistical problems. In this article, the SV-CIRP is formulated as a mixed-integer program with a nonlinear objective function. After a thorough analysis of the structure of the problem and its features, an exact algorithm for its solution is proposed. This exact algorithm requires only solutions of linear mixed-integer programs. Values of a savings-based heuristic for this problem are compared to the optimal values obtained for a set of some test problems. In general, the gap may get as large as 25%, which justifies the effort to continue exploring and developing exact and approximation algorithms for the SV-CIRP.
C.M. Meyer; Kok, A.L.; H Kopfer; Schutten, J.M.J.
2009-01-01
We analyze the problem of combined vehicle routing and break scheduling from a distributed decision making perspective. The problem of combined vehicle routing and break scheduling can be defined as the problem of finding vehicle routes to serve a set of customers such that a cost criterion is minimized and legal rules on driving and working hours are observed. In the literature, this problem is always analyzed from a central planning perspective. In practice, however, this problem is solved ...
An evolutionary algorithm for a real vehicle routing problem
Adamidis, P.
2012-01-01
Full Text Available The NP-hard Vehicle Routing Problem (VRP is central in the optimisation of distribution networks. Its main objective is to determine a set of vehicle trips of minimum total cost. The ideal schedule will efficiently exploit the company's recourses, service all customers and satisfy the given (mainly daily constraints. There have been many attempts to solve this problem with conventional techniques but applied to small-scale simplified problems. This is due to the complexity of the problem and the large volume of data to be processed. Evolutionary Algorithms are search and optimization techniques that are capable of confronting that kind of problems and reach a good feasible solution in a reasonable period of time. In this paper we develop an Evolutionary Algorithm in order to solve the VRP of a specific transportation company in Volos, Greece with different vehicle capacities. The algorithm has been tested with different configurations and constraints, and proved to be effective in reaching a satisfying solution for the company's needs.
The Vehicle Routing Problem with Time Windows and Temporal Dependencies
Rasmussen, Matias Sevel; Dohn, Anders Høeg; Larsen, Jesper
to be scheduled with a certain slack between them. They refer to the vehicle problem as having interdependent time windows. Temporal dependencies have been modeled for a home care routing problem in a mixed integer programming model (MIP) which was solved with a standard MIP solver. An application with general...... temporal dependencies is also found in machine scheduling. Column generation is used to solve the problem. The pricing problem is primarily solved heuristically by local search and occasionally to optimality using a standard solver on an integer programming formulation of the pricing problem. Two compact...... is novel as well. Finally, we introduce a new set of context-free benchmark instances which enables a thorough quantitative analysis and which we hope will facilitate future research in this area. The analysis shows that, even though the time-indexed model has some nice properties, it also retains its...
Efficient Intelligent Optimized Algorithm for Dynamic Vehicle Routing Problem
Jiangqing Wang
2011-11-01
Full Text Available In order to solve the dynamic vehicle routing problem (DVRP containing both dynamic network environment and real-time customer requests, an efficient intelligent optimized algorithm called IOA is proposed in this paper, which takes advantages of both global searching ability of evolutionary algorithms and local searching capability of ant colony algorithm. The proposed IOA incorporates ant colony algorithm for exploration and evolutionary algorithm for exploitation, and uses real-time information during the optimization process. In order to discuss the performance of the proposed algorithm, a mixed integral programming model for DVRP is formulated, and benchmark functions are constructed. Detailed simulation results and comparisons with the existed work show that the proposed IOA algorithm can achieve a higher performance gain, and is well suited to problems containing dynamic network environment and real-time customer requests.
Design of a Capacitive Flexible Weighing Sensor for Vehicle WIM System
Qing Li
2007-08-01
Full Text Available With the development of the Highway Transportation and Business Trade, vehicle weigh-in-motion (WIM technology has become a key technology and trend of measuring traffic loads. In this paper, a novel capacitive flexible weighing sensor which is light weight, smaller volume and easy to carry was applied in the vehicle WIM system. The dynamic behavior of the sensor is modeled using the Maxwell-Kelvin model because the materials of the sensor are rubbers which belong to viscoelasticity. A signal processing method based on the model is presented to overcome effects of rubber mechanical properties on the dynamic weight signal. The results showed that the measurement error is less than Ã���Â±10%. All the theoretic analysis and numerical results demonstrated that appliance of this system to weigh in motion is feasible and convenient for traffic inspection.
Formulations and Branch-and-Cut Algorithms for the Generalized Vehicle Routing Problem
Bektas, Tolga; Erdogan, Günes; Røpke, Stefan
2011-01-01
The Generalized Vehicle Routing Problem (GVRP) consists of nding a set of routes for a number of vehicles with limited capacities on a graph with the vertices partitioned into clusters with given demands such that the total cost of travel is minimized and all demands are met. This paper offers four...
Design of Vehicle Routing by Integrating Optimization and Simulated Annealing Approach
Chwen-Tzeng; Su; Chikong; Hwang
2002-01-01
The vehicle routing problem (VRP) can be described as the problem of designing the optimal delivery or collection routes from one or several depots to a number of geographically scattered customers, subject to load constraints. The routing decision involves determining which of the demand s will be satisfied by each vehicle and what route each vehicle will follow in s erving its assigned demand in order to minimize total delivery cost. In this pap er, a methodology for the design of VRP by integrating...
A hybrid GA-TS algorithm for open vehicle routing optimization of coal mines material
Yu, S.W.; Ding, C.; Zhu, K.J. [China University of Geoscience, Wuhan (China)
2011-08-15
In the open vehicle routing problem (OVRP), the objective is to minimize the number of vehicles and the total distance (or time) traveled. This study primarily focuses on solving an open vehicle routing problem (OVRP) by applying a novel hybrid genetic algorithm and the Tabu search (GA-TS), which combines the GA's parallel computing and global optimization with TS's Tabu search skill and fast local search. Firstly, the proposed algorithm uses natural number coding according to the customer demands and the captivity of the vehicle for globe optimization. Secondly, individuals of population do TS local search with a certain degree of probability, namely, do the local routing optimization of all customer sites belong to one vehicle. The mechanism not only improves the ability of global optimization, but also ensures the speed of operation. The algorithm was used in Zhengzhou Coal Mine and Power Supply Co., Ltd.'s transport vehicle routing optimization.
The electric vehicle routing problem with partial charging and nonlinear charging function
Montoya, Alejandro; Guéret, Christelle; Mendoza, Jorge E.; Villegas, Juan
2015-01-01
Electric vehicle routing problems (eVRPs) extend classical routing problems to consider the limited driving range of electric vehicles. In general, this limitation is overcome by introducing planned detours to battery charging stations. Most existing eVRP models rely on one (or both) of the following assumptions: (i) the vehicles fully charge their batteries every time they reach a charging station, and (ii) the battery charge level is a linear function of the charging time. In practical situ...
Research on multi-objective emergency logistics vehicle routing problem under constraint conditions
Miaomiao Du; Hua Yi
2013-01-01
Purpose: Aim at choosing a relative good vehicle routing in emergency conditions under constraint conditions when disaster happens. Rapid response and rescue can save a lot of people. Design/methodology/approach: Modeling analysis: establishing a mathematical model of multi-objective emergency logistics vehicle routing problem. And in end of the paper, we intend to use genetic algorithms to solve the problem. Findings: Considering time requirement and cost limit both while choosing vehicle ro...
A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study
Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time
Alireza Goli
2015-09-01
Full Text Available Distribution and optimum allocation of emergency resources are the most important tasks, which need to be accomplished during crisis. When a natural disaster such as earthquake, flood, etc. takes place, it is necessary to deliver rescue efforts as quickly as possible. Therefore, it is important to find optimum location and distribution of emergency relief resources. When a natural disaster occurs, it is not possible to reach some damaged areas. In this paper, location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling is investigated. In this study, there is no need to visit all the places and some demand points receive their needs from the nearest possible location. The proposed study is implemented for some randomly generated numbers in different sizes. The preliminary results indicate that the proposed method was capable of reaching desirable solutions in reasonable amount of time.
The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations
Hiermann, Gerhard; Puchinger, Jakob; Røpke, Stefan;
2016-01-01
detours to recharging stations necessary, thus requiring efficient tour planning mechanisms in order to sustain the competitiveness of electric vehicles compared to conventional vehicles. We introduce the Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations (E......-FSMFTW) to model decisions to be made with regards to fleet composition and the actual vehicle routes including the choice of recharging times and locations. The available vehicle types differ in their transport capacity, battery size and acquisition cost. Furthermore, we consider time windows at customer...
REFINEMENTS OF THE COLUMN GENERATION PROCESS FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
Jesper LARSEN
2004-01-01
The Vehicle Routing Problem with Time Windows is a generalization of the well known capacity constrained Vehicle Routing Problem. A homogeneous fleet of vehicles has to service a set of customers. The service of the customers can only start within a well-defined time interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance). Currently the best approaches for determining optimal solutions are based on column generation and Branch-and-Bound, also known as Branch-and-Price. This paper presents two ideas for run-time improvements of the Branch-and-Price framework for the Vehicle Routing Problem with Time Windows. Both ideas reveal a significant potential for run-time refinements when speeding up an exact approach without compromising optimality.
DULLAERT, Wout
2000-01-01
In this paper we study the performance of Solomon’s (1987) sequential insertion heuristic |1, for Vehicle Routing Problems with Time Windows (VRPTWs) in which the number of customers per rout is small with respect to the customers’ time windows and the scheduling horizon. Solomon’s (1987) time insertion c12 (i, u, j) underestimates the additional time needed of inserting a new customer u between the depot, i= i0 and the first customer j in the partially constructed rout (i0= I, i1=j,i1,…,im)....
Two-Phase Bicriterion Search for Finding Fast and Efficient Electric Vehicle Routes
Goodrich, Michael T.; Pszona, Paweł
2014-01-01
The problem of finding an electric vehicle route that optimizes both driving time and energy consumption can be modeled as a bicriterion path problem. Unfortunately, the problem of finding optimal bicriterion paths is NP-complete. This paper studies such problems restricted to two-phase paths, which correspond to a common way people drive electric vehicles, where a driver uses one driving style (say, minimizing driving time) at the beginning of a route and another driving style (say, minimizi...
The waste collection vehicle routing problem with time windows in a city logistics context
Buhrkal, Katja Frederik; Larsen, Allan; Røpke, Stefan
2012-01-01
Collection of waste is an important logistic activity within any city. In this paper we study how to collect waste in an efficient way. We study the Waste Collection Vehicle Routing Problem with Time Window which is concerned with finding cost optimal routes for garbage trucks such that all garba...
Vehicle routing problems with alternative paths: an application to on-demand transportation
Garaix, Thierry; Artigues, Christian; Feillet, Dominique; Josselin, Didier
2010-01-01
The class of vehicle routing problems involves the optimization of freight or passenger transportation activities. These problems are generally treated via the representation of the road network as a weighted complete graph. Each arc of the graph represents the shortest route for a possible origin-destination connection. Several attributes can be deﬁned for one arc (travel time, travel cost . . . ), but the shortest route modelled by this arc is computed according to one single criterion, gen...
Genetic Algorithm and Tabu Search for Vehicle Routing Problems with Stochastic Demand
Ismail, Zuhaimy; Irhamah
2010-11-01
This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.
The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations
Hiermann, Gerhard; Puchinger, Jakob; Ropke, Stefan; Hartl, Richard F.
2016-01-01
International audience Due to new regulations and further technological progress in the field of electric vehicles, the research community faces the new challenge of incorporating the electric energy based restrictions into vehicle routing problems. One of these restrictions is the limited battery capacity which makes detours to recharging stations necessary, thus requiring efficient tour planning mechanisms in order to sustain the competitiveness of electric vehicles compared to conventio...
A Routing Algorithm Based on Dynamic Forecast of Vehicle Speed and Position in VANET
Shukui Zhang; Haojing Huang
2013-01-01
Considering city road environment as the background, by researching GPSR greedy algorithm and the movement characteristics of vehicle nodes in VANET, this paper proposes the concept of circle changing trends angle in vehicle speed fluctuation curve and the movement domain and designs an SWF routing algorithm based on the vehicle speed point forecasted and the changing trends time computation. Simulation experiments are carried out through using a combination of NS-2 and VanetMobiSim software....
PERFORMANCE COMPARISON OF POSITION-BASED ROUTING PROTOCOLS IN VEHICLE-TOVEHICLE (V2V COMMUNICATION
SANJOY DAS
2011-01-01
Full Text Available Vehicular Ad hoc Networks (VANETs is the new wireless networking concept of the wireless ad hoc networks in the research community. Vehicle-to-Vehicle (V2V communication plays a significant role in providing a high level of safety and convenience to drivers and passengers. Routing in VANET is a major challenge and research area. Position based routing protocol has been identified to be suitable for VANETs because of frequently changed network topology and highly dynamic nature of vehicular nodes. Many position based routing protocols have been developed for routing messages in greedy orwarding way in VANETs. However, few of them are efficient when the network is highly dynamic. In this paper, we present an overview andqualitative comparison of existing position based routing protocols that are based on the position prediction of neighboring and destination nodes. We evaluate the performance metrics such as end-to-end delay and packet delivery ratio using NS-2 simulator.
Route Assessment for Unmanned Aerial Vehicle Based on Cloud Model
Xixia Sun
2014-01-01
Full Text Available An integrated route assessment approach based on cloud model is proposed in this paper, where various sources of uncertainties are well kept and modeled by cloud theory. Firstly, a systemic criteria framework incorporating models for scoring subcriteria is developed. Then, the cloud model is introduced to represent linguistic variables, and survivability probability histogram of each route is converted into normal clouds by cloud transformation, enabling both randomness and fuzziness in the assessment environment to be managed simultaneously. Finally, a new way to measure the similarity between two normal clouds satisfying reflexivity, symmetry, transitivity, and overlapping is proposed. Experimental results demonstrate that the proposed route assessment approach outperforms fuzzy logic based assessment approach with regard to feasibility, reliability, and consistency with human thinking.
ROUTE OPTIMIZATION TO INCREASE ENERGY EFFICIENCY AND REDUCE FUEL CONSUMPTION OF COMMUNAL VEHICLES
Nebojša M Jovičić
2010-01-01
Full Text Available Collection and transportation within the system of solid waste management may account more than 60% of the overall budget, most of which is for fuel costs. Furthermore, municipal vehicles have great environmental impact through exhaust gases emissions. The aim of this research was to estimate the potential for reduction of fuel consumption and thus the emission of CO2 through the communal vehicles route optimization. General methodology for route optimization is also presented. For the area under study, detailed field experimental research in the City of Kragujevac was conducted. Using GIS and GPS technology, whole municipally infrastructure for waste collection was scanned and all paths of communal tracks was recorded and allocated in developed database. Based on experimental and numerical results, one typical municipal vehicle route was analyzed by using ArcGis software. The obtained result indicates 2700 km of possible savings per year concerning one communal vehicle. In addition, the most fuel-economical route was extracted and compared with the original route, and with the routes extracted from criterions concerning the traffic time and shortest distance. According to available information for the City of Kragujevac and the results from this study, it was estimated that the total savings could be 20% in costs and the associated emissions.
Research on multi-objective emergency logistics vehicle routing problem under constraint conditions
Miaomiao Du
2013-03-01
Full Text Available Purpose: Aim at choosing a relative good vehicle routing in emergency conditions under constraint conditions when disaster happens. Rapid response and rescue can save a lot of people. Design/methodology/approach: Modeling analysis: establishing a mathematical model of multi-objective emergency logistics vehicle routing problem. And in end of the paper, we intend to use genetic algorithms to solve the problem. Findings: Considering time requirement and cost limit both while choosing vehicle routing when the disasters happens is meaningful. We can get a relative good result and give a guidance to rescue teams. Originality/value: Consider cost and time objectives and kinds of realistic conditions (such as the road congestion in the model when solving the problem, having expanded the theory scope.
Murata, Tadahiko; Itai, Ryota
2008-01-01
In this chapter, we proposed a local search that can be used in a two-fold EMO algorithm for multiple-objective VRPs with different demands. The simulation results show that the proposed method have the fine effectiveness to enhance the similarity of obtained routes for vehicles. Although the local search slightly deteriorates the maximum duration, it improves the similarity of the routes that may decrease the possibility of getting lost the way of drivers. If drivers get lost their ways duri...
Optimized Crossover Genetic Algorithm for Vehicle Routing Problem with Time Windows
H. Nazif
2010-01-01
Full Text Available Problem statement: In this study, we considered the application of a genetic algorithm to vehicle routing problem with time windows where a set of vehicles with limits on capacity and travel time are available to service a set of customers with demands and earliest and latest time for serving. The objective is to find routes for the vehicles to service all the customers at a minimal cost without violating the capacity and travel time constraints of the vehicles and the time window constraints set by the customers. Approach: We proposed a genetic algorithm using an optimized crossover operator designed by a complete undirected bipartite graph that finds an optimal set of delivery routes satisfying the requirements and giving minimal total cost. Various techniques have also been introduced into the proposed algorithm to further enhance the solutions quality. Results: We tested our algorithm with benchmark instances and compared it with some other heuristics in the literature. The results showed that the proposed algorithm is competitive in terms of the quality of the solutions found. Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. From the results, it can be concluded that the proposed algorithm is competitive when compared with other heuristics in the literature.
Single-Commodity Vehicle Routing Problem with Pickup and Delivery Service
Goran Martinovic
2008-01-01
Full Text Available We present a novel variation of the vehicle routing problem (VRP. Single commodity cargo with pickup and delivery service is considered. Customers are labeled as either cargo sink or cargo source, depending on their pickup or delivery demand. This problem is called a single commodity vehicle routing problem with pickup and delivery service (1-VRPPD. 1-VRPPD deals with multiple vehicles and is the same as the single-commodity traveling salesman problem (1-PDTSP when the number of vehicles is equal to 1. Since 1-VRPPD specializes VRP, it is hard in the strong sense. Iterative modified simulated annealing (IMSA is presented along with greedy random-based initial solution algorithm. IMSA provides a good approximation to the global optimum in a large search space. Experiment is done for the instances with different number of customers and their demands. With respect to average values of IMSA execution times, proposed method is appropriate for practical applications.
Multidimentional Self-organization for Online Time-Constrained Vehicle Routing Problems
ZEDDINI, B; ZARGAYOUNA, M
2010-01-01
Vehicle Routing problems are highly complex problems for which different Artificial Intelligence techniques have been used. In this paper, we propose two agent-oriented self-organization models for the dynamic version of the problem with time windows. The first model relies on a spatial representation, and the second is based on a space-time representation of the agents' action zones, which are able to maintain a good distribution of the vehicles on the environment. This distribution provides...
Opportunity costs calculation in agent-based vehicle routing and scheduling
Mes, Martijn; Heijden, van der, C.A.M.; Schuur, Peter
2006-01-01
In this paper we consider a real-time, dynamic pickup and delivery problem with timewindows where orders should be assigned to one of a set of competing transportation companies. Our approach decomposes the problem into a multi-agent structure where vehicle agents are responsible for the routing and scheduling decisions and the assignment of orders to vehicles is done by using a second-price auction. Therefore the system performance will be heavily dependent on the pricing strategy of the veh...
Hybrid tabu search for the multi-depot vehicle routing problem
Hu, Shan-Liang
2010-07-01
A hybrid tabu search for the multi-depot vehicle routing problem is considered in this paper. The purpose of the proposed approach is to decrease the number of used vehicles and the total travel cost. An extensive numerical experiment was performed on benchmark problem instances available in literature, the computational results are presented to show the high effectiveness and performance of the proposed approaches.
Control strategies for the vehicle routing problem applied to medical emergencies
Chini, Giorgia
2014-01-01
This thesis deals with dynamic Multi-Vehicle Routing Problem (MVRP) in both deterministic and stochastic scenarios. The objective of the MVRP is to find the best paths for a fleet of vehicles, with the aim of visiting a set of targets. Based on the Cooperative Receding Horizon (CRH) approach proposed by Cassandras et al.(CRH) for the Euclidean case, this thesis: i) presents another algorithm that is more efficient with clustered targets (tCRH); ii) illustrates an algorithm that ex...
Modelling of the optimal vehicle route in terrain in emergency situations using GIS data
Most navigation systems in transport are oriented towards the search for optimal paths (shortest or fastest), using vector GIS data. At the time of natural disasters and emergency situations is necessary to consider roads and terrain for transport. This article is focused on finding optimal routes in terrain, which contains a number of point, line and area obstacles. The most frequent point obstacles are trees in the forest. The paper analyzes the typical structure of tree stands in the forest, their characteristics in GIS databases, as well as dimensional parameters of vehicles moving in the forest. The quality of these data is a prerequisite for finding routes between point obstacles. Searching for the fastest or shortest route of the vehicle described in this article is based on the use of the relationship between the Delaunay triangulation and Voronoi graph, the application of Dijkstra's algorithm and the optimization of fractional line. The above-mentioned methods are also exploitable for searching for the shortest route of movement among line obstructions and area obstructions, such route can be apprehended as the joining of points defining impassable terrain. In such a case, the condition must be met that the distance of terminal points of joins has to be adjusted to the extent that it will be shorter than a vehicle width increased by safe margin
Modelling of the optimal vehicle route in terrain in emergency situations using GIS data
Rybansky, M.
2014-02-01
Most navigation systems in transport are oriented towards the search for optimal paths (shortest or fastest), using vector GIS data. At the time of natural disasters and emergency situations is necessary to consider roads and terrain for transport. This article is focused on finding optimal routes in terrain, which contains a number of point, line and area obstacles. The most frequent point obstacles are trees in the forest. The paper analyzes the typical structure of tree stands in the forest, their characteristics in GIS databases, as well as dimensional parameters of vehicles moving in the forest. The quality of these data is a prerequisite for finding routes between point obstacles. Searching for the fastest or shortest route of the vehicle described in this article is based on the use of the relationship between the Delaunay triangulation and Voronoi graph, the application of Dijkstra's algorithm and the optimization of fractional line. The above-mentioned methods are also exploitable for searching for the shortest route of movement among line obstructions and area obstructions, such route can be apprehended as the joining of points defining impassable terrain. In such a case, the condition must be met that the distance of terminal points of joins has to be adjusted to the extent that it will be shorter than a vehicle width increased by safe margin.
Refinements of the column generation process for the Vehicle Routing Problem with Time Windows
Larsen, Jesper
2004-01-01
interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance) with respect to the above mentioned constraints. Currently the best approaches for determining optimal solutions are based on column generation and Branch...
Opportunity costs calculation in agent-based vehicle routing and scheduling
Mes, Martijn; Heijden, van der Matthieu; Schuur, Peter
2006-01-01
In this paper we consider a real-time, dynamic pickup and delivery problem with timewindows where orders should be assigned to one of a set of competing transportation companies. Our approach decomposes the problem into a multi-agent structure where vehicle agents are responsible for the routing and
Relative Performance of Certain Meta Heuristics on Vehicle Routing Problem with Time Windows
Sandhya
2015-11-01
Full Text Available —Solving Vehicle Routing Problem (VRP and its variants arise in many real life distribution systems. Classical VRP can be described as the problem of finding minimum cost routes with identical vehicles having fixed capacity which starts from a depot and reaches a number of customers with known demands with the proviso that each route starts and ends at the depot and the demand of each customer does not exceed the vehicle capacity is met. One of the generalizations of standard VRP is Vehicle Routing Problem with Time Windows (VRPTW with added complexity of serving every customer within a specified time window. Since VRPTW is a NP hard meta heuristics have often been designed for solving it. In this paper we compare the performance of Simulated Annealing (SA, genetic Algorithm (GA and Ant Colony Optimization (ACO for solving VRPTW based on their performance using different parameters taking total travel distance as the objective to be minimized. The results indicate that ACO is in general slightly more efficient then SA and GA.
Routing of Electric Vehicles: Case Study of City Distribution in Copenhagen
Linde, Esben; Larsen, Allan; Nørrelund, Anders Vedsted;
. References [1] T. van Rooijen and H. Quak, “Local impacts of a new urban consolidation centre – the case of Binnenstadservice.nl,” Procedia - Social and Behavioral Sciences, vol. 2, no. 3, pp. 5967–5979, Jan. 2010. [2] S. Erdogan and E. Miller-Hooks, “A Green Vehicle Routing Problem,” Transportation Research...
Chlorpyrifos (CPF) is a commonly used organophosphorus pesticide. A number of toxicity and mechanistic studies have been conducted in animals, where CPF has been administered via a variety of different exposure routes and dosing vehicles. This study compared chlorpyrifos (CPF) pharmacokinetics using oral, intravenous (IV), and subcutaneous (SC) exposure routes and corn oil, saline/Tween 20, and dimethyl sulfoxide (DMSO) as dosing vehicles. Two groups of rats were co-administered target doses (5 mg/kg) of CPF and isotopically labeled CPF (L-CPF). One group was exposed by both oral (CPF) and IV (L-CPF) routes using saline/Tween 20 vehicle; whereas, the second group was exposed by the SC route using two vehicles, corn oil (CPF) and DMSO (L-CPF). A third group was only administered CPF by the oral route in corn oil. For all treatments, blood and urine time course samples were collected and analyzed for 3,5,6-trichloro-2-pyridinol (TCPy), and isotopically labeled 3,5,6-trichloro-2-pyridinol (L-TCPy). Peak TCPy/L-TCPy concentrations in blood (20.2 μmol/l), TCPy/L-TCPy blood AUC (94.9 μmol/l h), and percent of dose excreted in urine (100%) were all highest in rats dosed orally with CPF in saline/Tween 20 and second highest in rats dosed orally with CPF in corn oil. Peak TCPy concentrations in blood were more rapidly obtained after oral administration of CPF in saline/Tween 20 compared to all other dosing scenarios (>1.5 h). These results indicate that orally administered CPF is more extensively metabolized than systemic exposures of CPF (SC and IV), and vehicle of administration also has an effect on absorption rates. Thus, equivalent doses via different routes and/or vehicles of administration could potentially lead to different body burdens of CPF, different rates of bioactivation to CPF-oxon, and different toxic responses. Simulations using a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model for CPF are consistent with these possibilities
C Hauman
2014-06-01
Full Text Available The vehicle routing problem with time windows is a widely studied problem with many real-world applications. The problem considered here entails the construction of routes that a number of identical vehicles travel to service different nodes within a certain time window. New benchmark problems with multi-objective features were recently suggested in the literature and the multi-objective optimisation cross-entropy method is applied to these problems to investigate the feasibility of the method and to determine and propose reference solutions for the benchmark problems. The application of the cross-entropy method to the multi-objective vehicle routing problem with soft time windows is investigated. The objectives that are evaluated include the minimisation of the total distance travelled, the number of vehicles and/or routes, the total waiting time and delay time of the vehicles and the makespan of a route.
Vehicle Routing Problem with Backhaul, Multiple Trips and Time Window
Johan Oscar Ong
2011-01-01
Full Text Available Transportation planning is one of the important components to increase efficiency and effectiveness in the supply chain system. Good planning will give a saving in total cost of the supply chain. This paper develops the new VRP variants’, VRP with backhauls, multiple trips, and time window (VRPBMTTW along with its problem solving techniques by using Ant Colony Optimization (ACO and Sequential Insertion as initial solution algorithm. ACO is modified by adding the decoding process in order to determine the number of vehicles, total duration time, and range of duration time regardless of checking capacity constraint and time window. This algorithm is tested by using set of random data and verified as well as analyzed its parameter changing’s. The computational results for hypothetical data with 50% backhaul and mix time windows are reported.
Intelligent Iterated Local Search Methods for Solving Vehicle Routing Problem with Different Fleets
无
2007-01-01
To solve vehicle routing problem with different fleets, two methodologies are developed. The first methodology adopts twophase strategy. In the first phase, the improved savings method is used to assign customers to appropriate vehicles. In the second phase, the iterated dynasearch algorithm is adopted to route each selected vehicle with the assigned customers. The iterated dynasearch algorithm combines dynasearch algorithm with iterated local search algorithm based on random kicks. The second methodplogy adopts the idea of cyclic transfer which is performed by using dynamic programming algorithm, and the iterated dynasearch algorithm is also embedded in it. The test results show that both methodologies generate better solutions than the traditional method, and the second methodology is superior to the first one.
Research of Multi-Depot Vehicle Routing Problem by Cellular Ant Algorithm
Yuanzhi Wang
2013-07-01
Full Text Available The Multi-Depot Vehicle Routing Problem (MDVRP is a generalization of SDVRP, in which multiple vehicles start from multiple depots and return to their original depots at the end of their assigned tours. The MDVRP is NP-hard, therefore, the development of heuristic algorithms for this problem class is of primary interest. This paper solves Multi-Depot Vehicle Routing Problem with Cellular Ant Algorithm which is a new optimization method for solving real problems by using both the evolutionary rule of cellular, graph theory and the characteristics of ant colony optimization. The simulation experiment shows that the Cellular Ant Algorithm is feasible and effective for the MDVRP. The clarity and simplicity of the Cellular Ant Algorithm is greatly enhanced to ant colony optimization.
Disjunctive cuts in a branch-and-price algorithm for the capacitated vehicle routing problem
Røpke, Stefan
This talk presents computational results that show the usefulness of the general-purpose valid inequalities disjunctive cuts when applied to the CVRP. Results indicate that the disjunctive cuts are able to reduce the gap between lower bound and upper bound more than state-of-the-art problem speci...... specific inequalities. Results also indicate that introducing the cuts leads to a smaller branch and bound tree and faster solution times overall.......This talk presents computational results that show the usefulness of the general-purpose valid inequalities disjunctive cuts when applied to the CVRP. Results indicate that the disjunctive cuts are able to reduce the gap between lower bound and upper bound more than state-of-the-art problem...
A Column Generation Approach to the Capacitated Vehicle Routing Problem with Stochastic Demands
Christiansen, Christian Holk; Lysgaard, Jens
CVRPSD can be formulated as a Set Partitioning Problem. We show that, under the above assumptions on demands, the associated column generation subproblem can be solved using a dynamic programming scheme which is similar to that used in the case of deterministic demands. To evaluate the potential of our...... approach we have embedded this column generation scheme in a branch-and-price algorithm. Computational experiments on a large set of test instances show promising results....
Models and Methods for the City Logistics: The Two-Echelon Capacitated Vehicle Routing Problem
Gonzalez-Feliu, Jesus
2008-01-01
La distribution de marchandises est un secteur en constant développement et constitue un facteur économique important. Par contre, dans les villes, il contribue notamment aux problèmes de congestion, pollution, bruit et d'autres dérangements à la population des villes. Pour faire face à ces problèmes, une nouvelle discipline est née à la fin du XXe siècle, la " City Logistics ", qui a comme objectifs principaux la réduction de la congestion, la pollution et le bruit occasionné par le transpor...
Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows
Bent, Russell W [Los Alamos National Laboratory
2010-01-01
This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositions which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.
A Multi-objective Optimization Model for Planning Unmanned Aerial Vehicle Cruise Route
Xiaofeng Liu
2016-06-01
Full Text Available The use of unmanned aerial vehicles (UAVs was introduced to monitor a traffic situation and the respective cruise route optimization problem was given. Firstly, a multi-objective optimization model was proposed, which considered two scenarios: the first scenario was that there were enough UAVs to monitor all the targets, while the second scenario was that only some targets could be monitored due to a lack of UAVs. A multi-objective evolutionary algorithm was subsequently proposed to plan the UAV cruise route. Next, a route planning experiment, using the Microdrones md4-1000 UAV, was conducted and a UAV route planning case was studied. The experiment showed that the UAV actual flight route was almost consistent with the planned route. The case study showed that, compared with the initial optimal solutions, the optimal total UAV cruise distance and the number of UAVs used in scenario 1 decreased by 41.65% and 40.00%, respectively. Meanwhile, the total UAV cruise distance and the number of targets monitored in scenario 2 reduced by 15.75% and increased by 27.27%, respectively. In addition, a comparison study with other algorithms was conducted, while the optimization results were also improved. This demonstrated that the proposed UAV cruise route planning model was effective.
A HYBRID GENETIC ALGORITHM IMPLEMENTATION FOR VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
Muhammad Faisal Ibrahim
2016-01-01
Full Text Available This article is related to approach development in order to determine the most appropriate route for bottled water delivery from warehouse to retail from particular boundaries such as a limit on number of vehicle, vehicle capacity, and time windows to each retail. A mathematical model of VRPTW is adopted to solve the problem. Malang is one of the drinking water production centers in Indonesia, definitely it will be difficult for the company to determine the optimal delivery route with the existing restrictions. In this research hybrid genetic algorithm is use to determine the route shipping companies with the Java programming language. After analyzing the results obtained show that the results of the implementation of hybrid genetic algorithm is better than the company actual route. Moreover, authors also analyze the effect the number of iterations for the computation time, and the influence the number of iterations for the fitness value or violation. This algorithm can be applied for the routing and the result obtained is an optimal solution
Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment
Barnawi, Waleed T.
Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned
The Edge Set Cost of the Vehicle Routing Problem with Time Windows
Reinhardt, Line Blander; Jepsen, Mads Kehlet; Pisinger, David
2016-01-01
We consider an important generalization of the vehicle routing problem with time windows in which a fixed cost must be paid for accessing a set of edges. This fixed cost could reflect payment for toll roads, investment in new facilities, the need for certifications, and other costly investments....... The certifications and investments impose a cost for the company while they also give unlimited usage of a set of roads to all vehicles belonging to the company. This violates the traditional assumption that the path between two destinations is well defined and independent of other choices. Different...
Luo, Zhixin; Qin, Hu; Zhu, Wenbin; Lim, Andrew
2014-01-01
This paper addresses a new vehicle routing problem that simultaneously involves time windows, split collection and linear weight-related cost, which is a generalization of the split delivery vehicle routing problem with time windows (SDVRPTW). This problem consists of determining least-cost vehicle routes to serve a set of customers while respecting the restrictions of vehicle capacity and time windows. The travel cost per unit distance is a linear function of the vehicle weight and the custo...
An Angle-Based Crossover Tabu Search for Vehicle Routing Problem
Yang, Ning; Li, Ping; Li, Mingsen
An improved tabu search - crossover tabu search (CTS) is presented which adopt the crossover operator of the genetic algorithm as the diversification strategy, and selecting elite solutions as the intensification strategies. To improve the performances, the angle-based idea of the sweep heuristic is used to confirm the neighborhood, and an object function with punishment. The angle-based CTS is applied for the vehicle routing problem. The simulating results which compared the tradition sweep heuristic and the standard tabu search shows the results got by angle-based CTS are better than those got by other two heuristics. The experiment shows the angle-based CTS has good performance on the vehicle routing problem.
Branch and price for the time-dependent vehicle routing problem with time windows
Dabia, Said; Van Woensel, Tom; De Kok, Ton;
2013-01-01
This paper presents a branch-and-price algorithm for the time-dependent vehicle routing problem with time windows (TDVRPTW). We capture road congestion by considering time-dependent travel times, i.e., depending on the departure time to a customer, a different travel time is incurred. We consider...... the variant of the TDVRPTW where the objective is to minimize total route duration and denote this variant the duration minimizing TDVRPTW (DM-TDVRPTW). Because of time dependency, vehicles' dispatch times at the depot are crucial as road congestion might be avoided. Because of its complexity, all...... means of column generation, and a tailored labeling algorithm is used to solve the pricing problem. We introduce new dominance criteria that allow more label dominance. For our numerical results, we modified Solomon's data sets by adding time dependency. Our algorithm is able to solve about 63% of the...
A framework for the interactive resolution of multi-objective vehicle routing problems
Geiger, Martin Josef
2008-01-01
The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.
A Hybrid Genetic Algorithm for Vehicle Routing Problem with Complex Constraints
CHEN Yan; LU Jun; LI Zeng-zhi
2006-01-01
Most research on the Vehicle Routing Problem (VRP) is focused on standard conditions, which is not suitable for specific cases. A Hybrid Genetic Algorithm is proposed to solve a Vehicle Routing Problem (VRP) with complex side constraints. A novel coding method is designed especially for side constraints. A greedy algorithm combined with a random algorithm is introduced to enable the diversity of the initial population, as well as a local optimization algorithm employed to improve the searching efficiency. In order to evaluate the performance, this mechanism has been implemented in an oil distribution center, the experimental and executing results show that the near global optimal solution can be easily and quickly obtained by this method, and the solution is definitely satisfactory in the VRP application.
The United States Postal Service (USPS) has ordered 500 light-duty electric carrier route vehicles (ECRV) mostly for their delivery carriers to use in several California locations. The 500 ECRVs have been defined as a demonstration fleet to support a decision of potentially ordering 5,500 additional ECRVs. Several different test methods are being used by the USPS to evaluate the 500-vehicle deployment. One of these test methods is the ECRV Customer Acceptance Test Program at Fountain Valley, California. Two newly manufactured ECRVs were delivered to the Fountain Valley Post Office and eighteen mail carriers primarily drove the ECRVs on ''park and loop'' mail delivery routes for a period of 2 days each. This ECRV testing consisted of 36 route tests, 18 tests per vehicle. The 18 mail carriers testing the ECRVs were surveyed for the opinions on the performance of the ECRVs. The U.S. Department of Energy, through its Field Operations Program, is supporting the USPS's ECRV testing activities both financially and with technical expertise. As part of this support, Field Operations Program personnel at the Idaho National Engineering and Environmental Laboratory have compiled this report based on the data generated by the USPS and its testing contractor (Ryerson, Master and Associates, Inc.) During the 36 route tests, the two test vehicles were driven a total of 474 miles, averaging 13 mile per test. The distance of the 36 route tests ranged from 4 to 34 miles. Both miles driven and State-of-Charge (SOC) data was collected for only 28 of the route tests. During these 28 tests, the ECRVs were driven a total of 447 miles. The SOC used during the 28 tests averaged a 41% decrease and the average distance driven was 16 miles. This suggests that a 16-mile route uses almost half of the ECRV's battery energy. The 18 carriers also rated 12 ECRV traits that included the physical design of the ECRVs as well as their performance. Based on a scale of 1 being the lowest and 5 being
A set-covering based heuristic algorithm for the periodic vehicle routing problem.
Cacchiani, V; Hemmelmayr, V C; Tricoire, F
2014-01-30
We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems. PMID:24748696
Wen, Min; Krapper, Emil; Larsen, Jesper;
2011-01-01
The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown...... week. Computational results show that the aggregation procedure and the decomposition strategy are very effective in solving this large scale problem, and our solutions are superior to the industrial solutions given the constraints considered in this work....
An apprenticeship learning hyper-heuristic for vehicle routing in HyFlex
Asta, Shahriar; Özcan, Ender
2014-01-01
Apprenticeship learning occurs via observations while an expert is in action. A hyper-heuristic is a search method or a learning mechanism that controls a set of low level heuristics or combines different heuristic components to generate heuristics for solving a given computationally hard problem. In this study, we investigate into a novel apprenticeship-learning-based approach which is used to automatically generate a hyper-heuristic for vehicle routing. This approach itself can be considere...
Pricing routines for vehicle routing with time windows on road networks
Letchford, Adam; Nasiri, Saeideh D.
2014-01-01
Several very effective exact algorithms have been developed for vehicle routing problems with time windows. Unfortunately, most of these algorithms cannot be applied to instances that are defined on road networks, because they implicitly assume that the cheapest path between two customers is equal to the quickest path. Garaix and coauthors proposed to tackle this issue by first storing alternative paths in an auxiliary multi-graph, and then using that multi-graph within a branch-and-price alg...
Acceleration of Lagrangian Method for the Vehicle Routing Problem with Time Windows
Abbas Seifi,; Hadi Karimi
2012-01-01
The analytic center cutting plane method (ACCPM) is one of successful methods to solve nondifferentiable optimization problems. In this paper, ACCPM is used to accelerate Lagrangian relaxation procedure for solving a vehicle routing problem with time windows (VRPTW). First, a basic cutting plane algorithm and its relationship with a column generation technique is clarified. Then, the proposed method based on ACCPM is explained as a stabilization technique for Lagrangian relaxation. Both appro...
Qi Hu
2013-04-01
Full Text Available State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and the judgment of the local optimal solution. Based on these, a hybrid chaos-particle swarm optimization algorithm (HPSO is proposed to solve VRPTW. The chaos algorithm is employed to re-initialize the particle swarm. An efficient insertion heuristic algorithm is also proposed to build the valid vehicle route in the particle decoding process. A particle swarm premature convergence judgment mechanism is formulated and combined with the chaos algorithm and Gaussian mutation into HPSO when the particle swarm falls into the local convergence. Extensive experiments are carried out to test the parameter settings in the insertion heuristic algorithm and to evaluate that they are corresponding to the data’s real-distribution in the concrete problem. It is also revealed that the HPSO achieves a better performance than the other state-of-the-art algorithms on solving VRPTW.
Effects of Vehicle Number Feedback in Multi-Route Intelligent Traffic Systems
Dong, Chuanfei; Ma, Xu; Wang, Binghong
We first study dynamics of traffic flow with real-time information and the influence of a new feedback strategy named Vehicle Number Feedback Strategy (VNFS) in a multi-route scenario in which dynamic information can be generated and displayed on the board (the board refers to a variable message sign where information on the routes is displayed) to guide road users to make a choice. In a multi-route scenario, our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting vehicle number feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e. Travel Time Feedback Strategy (TTFS), Mean Velocity Feedback Strategy (MVFS) and Congestion Coefficient Feedback Strategy (CCFS). We also discuss the influence of expected arrival rate (Vp) at the entrance on the average flux of each route, and we find that the flux adopting VNFS is always the largest at each Vp value among these four feedback strategies.
Similarity-Based Prediction of Travel Times for Vehicles Traveling on Known Routes
Tiesyte, Dalia; Jensen, Christian Søndergaard
2008-01-01
, historical data in combination with real-time data may be used to predict the future travel times of vehicles more accurately, thus improving the experience of the users who rely on such information. We propose a Nearest-Neighbor Trajectory (NNT) technique that identifies the historical trajectory that is......The use of centralized, real-time position tracking is proliferating in the areas of logistics and public transportation. Real-time positions can be used to provide up-to-date information to a variety of users, and they can also be accumulated for uses in subsequent data analyses. In particular...... trajectories of vehicles that travel along known routes. In empirical studies with real data from buses, we evaluate how well the proposed distance functions are capable of predicting future vehicle movements. Second, we propose a main-memory index structure that enables incremental similarity search and that...
Improved Multi-Agent System for the Vehicle Routing Problem with Time Windows
DAN Zhenggang; CAI Linning; ZHENG Li
2009-01-01
The vehicle routing problem with time windows (VRPTW) involves assigning a fleet of limited ca-pacity vehicles to serve a set of customers without violating the capacity and time constraints. This paper presents a multi-agent model system for the VRPTW based on the internal behavior of agents and coordina-tion among the agents. The system presents a formal view of coordination using the traditional contract-net protocol (CNP) that relies on the basic loop of agent behavior for order receiving, order announcement, bid calculation, and order scheduling followed by order execution. An improved CNP method based on a vehicle selection strategy is used to reduce the number of negotiations and the negotiation time. The model is vali-dated using Solomon's benchmarks, with the results showing that the improved CNP uses only 30% as many negotiations and only 70% of the negotiation time of the traditional CNP.
Yu Lin; Tianyi Xu; Zheyong Bian
2015-01-01
High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT) strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, fr...
E. Osaba; Yang, Xin-She; Diaz, F.; Onieva, E.; Masegosa, A. D.; A. Perallos
2016-01-01
A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a bench...
Wan-Yu Liu; Chun-Cheng Lin; Ching-Ren Chiu; You-Song Tsao; Qunwei Wang
2014-01-01
Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, a...
Michael Drexl; Julia Rieck; Thomas Sigl; Bettina Press
2013-01-01
This paper studies a simultaneous vehicle and crew routing and scheduling problem arising in long-distance road transport in Europe: Pickup-and-delivery requests have to be fulfilled over a multi-period planning horizon by a heterogeneous fleet of trucks and drivers. Typically, in the vehicle routing literature, a fixed assignment of a driver to a truck is assumed. In our approach, we abandon this assumption and allow truck/driver changes at geographically dispersed relay stations. This offer...
Son, Le Hoang; Louati, Amal
2016-06-01
Municipal Solid Waste (MSW) collection is a necessary process in any municipality resulting in the quality-of-life, economic aspects and urban structuralization. The intrinsic nature of MSW collection relates to the development of effective vehicle routing models that optimize the total traveling distances of vehicles, the environmental emission and the investment costs. In this article, we propose a generalized vehicle routing model including multiple transfer stations, gather sites and inhomogeneous vehicles in time windows for MSW collection. It takes into account traveling in one-way routes, the number of vehicles per m(2) and waiting time at traffic stops for reduction of operational time. The proposed model could be used for scenarios having similar node structures and vehicles' characteristics. A case study at Danang city, Vietnam is given to illustrate the applicability of this model. The experimental results have clearly shown that the new model reduces both total traveling distances and operational hours of vehicles in comparison with those of practical scenarios. Optimal routes of vehicles on streets and markets at Danang are given. Those results are significant to practitioners and local policy makers. PMID:27036996
Ant colony system (ACS with hybrid local search to solve vehicle routing problems
Suphan Sodsoon
2016-02-01
Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.
Vehicle Routing Problem for Fashion Supply Chains with Cross-Docking
Zhi-Hua Hu
2013-01-01
Full Text Available Cross-docking, as a strategy to reduce lead time and enhance the efficiency of the fashion supply chain, has attracted substantial attention from both the academy and the industry. Cross-docking is a critical part of many fashion and textiles supply chains in practice because it can help to achieve many supply chain strategies such as postponement. We consider a model where there are multiple suppliers and customers in a single cross-docking center. With such a model setting, the issue concerning the coordinated routing between the inbound and outbound routes is much more complex than many traditional vehicle routing problems (VRPs. We formulate the optimal route selection problems from the suppliers to the cross-docking center and from the cross-docking center to the customers as the respective VRPs. Based on the relationships between the suppliers and the customers, we integrate the two VRP models to optimize the overall traveling time, distance, and waiting time at the cross-docking center. In addition, we propose a novel mixed 0/1 integer linear programming model by which the complexity of the problem can be reduced significantly. As demonstrated by the simulation analysis, our proposed model can be solved very efficiently by a commonly used optimization software package.
Xu, Sheng-Hua; Liu, Ji-Ping; Zhang, Fu-Hao; Wang, Liang; Sun, Li-Jian
2015-01-01
A combination of genetic algorithm and particle swarm optimization (PSO) for vehicle routing problems with time windows (VRPTW) is proposed in this paper. The improvements of the proposed algorithm include: using the particle real number encoding method to decode the route to alleviate the computation burden, applying a linear decreasing function based on the number of the iterations to provide balance between global and local exploration abilities, and integrating with the crossover operator of genetic algorithm to avoid the premature convergence and the local minimum. The experimental results show that the proposed algorithm is not only more efficient and competitive with other published results but can also obtain more optimal solutions for solving the VRPTW issue. One new well-known solution for this benchmark problem is also outlined in the following. PMID:26343655
Wan-Yu Liu
2014-07-01
Full Text Available Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP. This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.
Solving the Vehicle Routing Problem with Stochastic Demands via Hybrid Genetic Algorithm-Tabu Search
Z. Ismail
2008-01-01
Full Text Available This study considers a version of the stochastic vehicle routing problem where customer demands are random variables with known probability distribution. A new scheme based on a hybrid GA and Tabu Search heuristic is proposed for this problem under a priori approach with preventive restocking. The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities resulted.
A P-Based Hybrid Evolutionary Algorithm for Vehicle Routing Problem with Time Windows
Yunyun Niu
2014-01-01
Full Text Available The ability to solve optimization problems using membrane algorithms is an important application of membrane computing. This work combines membrane systems and genetic operators to build an approximated algorithm for the vehicle routing problem with time windows. The algorithm is based on a tissue-like membrane structure combined with cell separation rules and communication rules; during such processes membranes collect and disperse information. Genetic operators are used as the system's subalgorithms. We also design a special improvement strategy to speed up the search process in subsystems. The experimental results show that the solution quality from the proposed algorithm is competitive with other heuristic or metaheuristic algorithms in the literature.
Clique inequalities applied to the vehicle routing problem with time windows
Spoorendonk, Simon; Desaulniers, Guy
2010-01-01
This work presents an exact branch-cut-and-price algorithm for the vehicle routing problem with time windows (VRPTW) where the well-known clique inequalities are used as cutting planes defined on the set partitioning master problem variables. It shows how these cutting planes affect the dominance......, to our knowledge, this is a first attempt at incorporating for the VRPTW a set of valid inequalities specialized for the set partitioning polytope. Computational results show that the use of clique inequalities improves the lower bound at the root node of the search tree and reduces the number of...
A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems
Xuhao Zhang
2014-01-01
Full Text Available A framing link (FL based tabu search algorithm is proposed in this paper for a large-scale multidepot vehicle routing problem (LSMDVRP. Framing links are generated during continuous great optimization of current solutions and then taken as skeletons so as to improve optimal seeking ability, speed up the process of optimization, and obtain better results. Based on the comparison between pre- and postmutation routes in the current solution, different parts are extracted. In the current optimization period, links involved in the optimal solution are regarded as candidates to the FL base. Multiple optimization periods exist in the whole algorithm, and there are several potential FLs in each period. If the update condition is satisfied, the FL base is updated, new FLs are added into the current route, and the next period starts. Through adjusting the borderline of multidepot sharing area with dynamic parameters, the authors define candidate selection principles for three kinds of customer connections, respectively. Link split and the roulette approach are employed to choose FLs. 18 LSMDVRP instances in three groups are studied and new optimal solution values for nine of them are obtained, with higher computation speed and reliability.
Omprakash Kaiwartya
2015-01-01
Full Text Available A multiobjective dynamic vehicle routing problem (M-DVRP has been identified and a time seed based solution using particle swarm optimization (TS-PSO for M-DVRP has been proposed. M-DVRP considers five objectives, namely, geographical ranking of the request, customer ranking, service time, expected reachability time, and satisfaction level of the customers. The multiobjective function of M-DVRP has four components, namely, number of vehicles, expected reachability time, and profit and satisfaction level. Three constraints of the objective function are vehicle, capacity, and reachability. In TS-PSO, first of all, the problem is partitioned into smaller size DVRPs. Secondly, the time horizon of each smaller size DVRP is divided into time seeds and the problem is solved in each time seed using particle swarm optimization. The proposed solution has been simulated in ns-2 considering real road network of New Delhi, India, and results are compared with those obtained from genetic algorithm (GA simulations. The comparison confirms that TS-PSO optimizes the multiobjective function of the identified problem better than what is offered by GA solution.
Vanessa de Oliveira Ferreira
2012-08-01
Full Text Available In this work we consider a variant of the vehicle routing problem that allows the assignment of multiple deliverymen to one or more routes. A practical motivation for this variant arises, for example, in the distribution of beverages in highly dense urban areas, characterized by the difficulty in serving daily requests within regular working day hours with a single deliveryman per vehicle. We present a mathematical model and a savings algorithm in order to generate low cost routes that maximize the number of requests served in compliance with the maximum route time. The impact of the extra deliverymen on the solutions provided by the proposed heuristic is assessed by means of sets of generated examples based on classical instances of literature. It is also presented the results obtained by an adaptation of a tabu search approach from the literature.
Epps, M
2014-01-01
Solving the variants of the Vehicle Routing Problem (VRP) is invaluable to a huge range of businesses today. It allows for the calculation of efficient logistics routing which can drastically improve a firm’s competitiveness. As NP-hard combinatorial optimisation problems, they cannot be solved by exact methods: the solution space is simply too large for it to be evaluated in entirety in a reasonable timespan. Instead, metaheuristic algorithms, which produce reasonably good solutions much mor...
Modified artificial bee colony for the vehicle routing problems with time windows.
Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana
2016-01-01
The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW. PMID:27547672
Thummala, Prasanth; Zhang, Zhe; Andersen, Michael A. E.;
2014-01-01
converter for efficiently charging and discharging the capacitive actuator from 0 V to 2.5 kV and vice versa, respectively. The converter is used to drive a dielectric electro active polymer (DEAP) based capacitive incremental actuator, which has the potential to be used in automotive (e.g., EVs), space and...
Michael Drexl
2013-11-01
Full Text Available This paper studies a simultaneous vehicle and crew routing and scheduling problem arising in long-distance road transport in Europe: Pickup-and-delivery requests have to be fulfilled over a multi-period planning horizon by a heterogeneous fleet of trucks and drivers. Typically, in the vehicle routing literature, a fixed assignment of a driver to a truck is assumed. In our approach, we abandon this assumption and allow truck/driver changes at geographically dispersed relay stations. This offers greater planning flexibility and allows a better utilization of trucks, but also creates intricate interdependencies between trucks and drivers and requires the synchronization of their routes. A solution heuristic based on a two-stage decomposition of the problem is developed, taking into account European Union social legislation for drivers, and computational experiments using real-world data provided by a major German forwarder are presented and analyzed. The obtained results suggest that for the vehicle and driver cost structure prevalent in Western Europe and for transport requests that are not systematically acquired to complement one another, no cost savings are possible through simultaneous vehicle and crew routing and scheduling, although no formal proof of this fact is possible.
Tri Kusnandi Fazarudin
2015-12-01
Full Text Available Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW is a problem of finding an optimal route for a supplier. The supplier needs to deliver goods to a number of customers using the vehicles located in a number of depots. Each delivery must be done within the service time specified by each customer The vehicles used have a maximum limit on the amount of goods that can be loaded and the maximum time the vehicle may be used. MDVRPTW is one of the variations of Vehicle Routing Problem (VRP. There are various algorithms that have been used to solve VRP problems. Some of them are Genetic Algorithm (GA, Tabu Search, and Adaptive GA with Artificial Bee Colony. GA can solve the problem within a shorter time, but it is vulnerable to get trapped in a local optimum. A strategy to reduce the probability of it is to make the GA adaptive. In this research, MDVRPTW is solved with GA. To reduce the probability of getting trapped in a local optimum, the GA parameters are made adaptive using Fuzzy Logic Controller (FLC. Based on the results of this research, using FLC on GA causes the average of the solution to be better than the solution produced using GA without FLC.
Mahmoudi, Monirehalsadat; Zhou, Xuesong
2015-01-01
Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). This paper first proposes a new time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles carrying states within space-time transportation networks, so as to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested tr...
2013-01-01
Multi-echelon distribution systems and more precisely, optimization of LTL routes related to them is one of the most popular subjects in the last 5 years of vehicle routing research. Although a plethora of models, methods and visions is found, it is still difficult to compare them because they use different terminologies and some authors insist on the fact there are a multitude of close but different problems. This paper presents the main concepts of multi-echelon distribution with cross-dock...
Wang, Jiahai; Zhou, Ying; Wang, Yong; Zhang, Jun; Chen, C L Philip; Zheng, Zibin
2016-03-01
This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry. VRPSDPTW is an important logistics problem in closed-loop supply chain network optimization. VRPSDPTW exhibits multiobjective properties in real-world applications. In this paper, a general multiobjective VRPSDPTW (MO-VRPSDPTW) with five objectives is first defined, and then a set of MO-VRPSDPTW instances based on data from the real-world are introduced. These instances represent more realistic multiobjective nature and more challenging MO-VRPSDPTW cases. Finally, two algorithms, multiobjective local search (MOLS) and multiobjective memetic algorithm (MOMA), are designed, implemented and compared for solving MO-VRPSDPTW. The simulation results on the proposed real-world instances and traditional instances show that MOLS outperforms MOMA in most of instances. However, the superiority of MOLS over MOMA in real-world instances is not so obvious as in traditional instances. PMID:25794408
Khanian, Seyed Mohammad Shafi
2007-01-01
Vehicle Routing and Scheduling (VRS) constitute an important part of logistics management. Given the fact that the worldwide cost on physical distribution is evermore increasing, the global competition and the complex nature of logistics problems, one area, which determines the efficiency of all others, is the VRS activities. The application of Decision Support Systems (DSS) to assist logistics management with an efficient VRS could be of great benefit. Although the benefits of DSS in VRS are...
Thummala, Prasanth; Zhang, Zhe; Andersen, Michael A. E.; Maksimovic, Dragan; Sarban, Rahimullah
2014-01-01
This paper presents the design of a low input (24 V) and variable high output voltage (0-2.5 kV) bidirectional dc-dc converter for driving a capacitive actuator. The topology is a digitally controlled bidirectional flyback converter with a variable frequency control. The objective is, to design the converter for efficiently charging and discharging the capacitive actuator from 0 V to 2.5 kV and vice versa, respectively. The converter is used to drive a dielectric electro active polymer (DEAP)...
Yu Lin
2015-01-01
Full Text Available High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, frequency planning, and vehicle type choice in order to optimize the sum of the cost of transportation, inventory, and dispatch. To this end, we develop a mathematical model to describe the common frequency problem with vehicle type choice. Since the problem is NP hard, we develop a two-phase heuristic algorithm to solve the model. More specifically, an initial satisfactory solution is first generated through a greedy heuristic algorithm to maximize the ratio of the superior arc frequency to the inferior arc frequency. Following this, a tabu search (TS with limited search scope is used to improve the initial satisfactory solution. Numerical examples with different sizes establish the efficacy of our model and our proposed algorithm.
Frost, Karen L; van Roosmalen, Linda; Bertocci, Gina; Cross, Douglas J
2012-01-01
An overview of the current status of wheelchair transportation safety in fixed route and demand-responsive, non-rail, public transportation vehicles within the US is presented. A description of each mode of transportation is provided, followed by a discussion of the primary issues affecting safety, accessibility, and usability. Technologies such as lifts, ramps, securement systems, and occupant restraint systems, along with regulations and voluntary industry standards have been implemented with the intent of improving safety and accessibility for individuals who travel while seated in their wheeled mobility device (e.g., wheelchair or scooter). However, across both fixed route and demand-responsive transit systems a myriad of factors such as nonuse and misuse of safety systems, oversized wheeled mobility devices, vehicle space constraints, and inadequate vehicle operator training may place wheeled mobility device (WhMD) users at risk of injury even under non-impact driving conditions. Since WhMD-related incidents also often occur during the boarding and alighting process, the frequency of these events, along with factors associated with these events are described for each transit mode. Recommendations for improving WhMD transportation are discussed given the current state of PMID:22876731
A Novel Discrete Differential Evolution Algorithm for the Vehicle Routing Problem in B2C E-Commerce
Xia, Chao; Sheng, Ying; Jiang, Zhong-Zhong; Tan, Chunqiao; Huang, Min; He, Yuanjian
2015-12-01
In this paper, a novel discrete differential evolution (DDE) algorithm is proposed to solve the vehicle routing problems (VRP) in B2C e-commerce, in which VRP is modeled by the incomplete graph based on the actual urban road system. First, a variant of classical VRP is described and a mathematical programming model for the variant is given. Second, the DDE is presented, where individuals are represented as the sequential encoding scheme, and a novel reparation operator is employed to repair the infeasible solutions. Furthermore, a FLOYD operator for dealing with the shortest route is embedded in the proposed DDE. Finally, an extensive computational study is carried out in comparison with the predatory search algorithm and genetic algorithm, and the results show that the proposed DDE is an effective algorithm for VRP in B2C e-commerce.
Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication
KIM, J.
2010-11-01
Full Text Available Suggesting more efficient driving routes generate benefits not only for individuals by saving commute time, but also for society as a whole by reducing accident rates and social costs by lessening traffic congestion. In this paper, we suggest a new route search algorithm based on a genetic algorithm which is more easily installable into mutually communicating car navigation systems, and validate its usefulness through experiments reflecting real-world situations. The proposed algorithm is capable of searching alternative routes dynamically in unexpected events of system malfunctioning or traffic slow-downs due to accidents. Experimental results demonstrate that our algorithm searches the best route more efficiently and evolves with universal adaptability.
Exactly solving the Split Pickup and Split Delivery Vehicle Routing Problem on a bike-sharing system
Casazza, Marco
2016-01-01
We propose an exact methodology to solve the Split Pickup and Split Delivery Vehicle Routing Problem arising in bike-sharing systems: a bike-sharing system is a public service in which bicycles are stored in rack stations and made available for shared use to individuals on a short term basis. However, during peak hours, flows along particular direction are registered, leading to high risk of empty racks in departure stations, and full racks at destination. One of the solutions chosen by many ...
Julia Rieck
2013-05-01
Full Text Available In reverse logistics networks, products (e.g., bottles or containers have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1.
Wen, Min; Krapper, Emil; Larsen, Jesper;
things, predefined workdays, fixed starting time, maximum weekly working duration, break rule. The objective is to minimize the total delivery cost. The real-life case study is fi rst introduced and modelled as a mixed integer linear program. A multilevel variable neighborhood search heuristic is then......This paper addresses an integrated vehicle routing and driver scheduling problem arising at the largest fresh meat producer in Denmark. The problem consists of a one-week planning horizon, heterogeneous vehicles, and drivers with predefi ned work regulations. These regulations include, among other...... proposed for the problem. At the first level, the problem size is reduced through an aggregation procedure. At the second level, the aggregated weekly planning problem is decomposed into daily planning problems, each of which is solved by a variable neighborhood search. At the last level, the solution of...
Suphan Sodsoon
2014-06-01
Full Text Available This study aims to solve a Vehicle Routing Problem with Time Windows and Speed Limits (VRPTWSL, which has received considerable attention in recent years. The vehicle routing problem with time windows is an extension of the well-known Vehicle Routing Problem (VRP and involves a fleet of vehicles set of from a depot to serve a number of customers at different geographic locations with various demands within specific time and speed limits before returning to the depot eventually. To solve the problem, an efficient Saving Method-Max Min Ant System (Saving-MMAS with Local Search algorithm is applied. Using minimization of the total transportation costs as the objective of the extension VRPTWSL, a mathematic model is constructed. Finally, the Saving-MMAS algorithms indicated the good quality of the method in this problem.
Digital capacitance measuring system
1973-01-01
The hardware phase of a digital capacitance measuring system is presented with the major emphasis placed on the electrical design and operation. Test results are included of the three units fabricated. The system's interface is applicable to existing requirements for the space shuttle vehicle.
Bruno Santos Goulart
2014-09-01
Full Text Available An efficient combustion depends on many factors, such as injection, turbulence and ignition characteristics. With the improvement of internal combustion engines the turbulence intensity and internal pressure have risen, demanding more efficient and powerful ignition systems. In direct injection engines, the stratified charge resultant from the wall/air-guided or spray-guided system requires even more energy. The Paschen’s law shows that spark plug gap and mixture density are proportional to the dielectric rupture voltage. It is known that larger spark gaps promote higher efficiency in the internal combustion engines, since the mixture reaction rate rises proportionally. However, the ignition system must be adequate to the imposed gap, not only on energy, but also on voltage and spark duration. For the reported study in this work two test benches were built: a standard inductive ignition system and a capacitive discharge high energy ignition system, with variable voltage and capacitance. The influence of the important parameters energy and ignition voltage on the spark duration, as well as the electrode gap and shape were analyzed. It was also investigated the utilization of a coil with lower resistance and inductance values, as well as spark plugs with and without internal resistances.
Machado, Guilherme Bastos, Cordeiro de Melo, Tadeu Cavalcante; Leao, Raphael Riemke de Campos Cesar; Iaccarino, Fernando Aniello; Figueiredo Moreira, Marcia
2007-07-01
The Brazilian CNG light-duty vehicle fleet has currently reached more than 1,300,000 units. This growth increased in the late 1990's, when CNG was approved for use in passenger cars. In 2001, the IBAMA (Brazilian Institute for Environment and Natural Renewable Resources), concerned with this uncontrolled growth, published CONAMA (National Environmental Council, controlled by IBAMA) resolution 291, which establishes rules for CNG conversion kit environmental certification.This paper discusses the technological challenges for CNG-converted vehicles to comply with PROCONVE (Brazilian Program for Automotive Air Pollution Control) emission limits. In the 1980's, because of the oil crisis, Natural Gas (NG) emerged as a fuel with great potential to replace Diesel in heavy-duty vehicles. Some experiences were conducted for partial conversions from Diesel to NG (Diesel-gas). Other experiences using NG Otto Cycle buses were conducted in some cities, but have not expanded. Another technological route called 'Ottolization' (Diesel to Otto cycle convertion) appeared recently. Population increase and the great growth in vehicle fleet promote a constant concern with automotive emissions. More restrictive emission limits, high international oil prices, and the strategic interest in replacing Diesel imports, altogether form an interesting scenario for CNG propagation to public transportation in the main Brazilian metropolises.
Vehicle routing for the eco-efficient collection of household plastic waste
Bing, X.; Keizer, de M.; Bloemhof, J.M.; Vorst, van der J.G.A.J.
2014-01-01
Plastic waste is a special category of municipal solid waste. Plastic waste collection is featured with various alternatives of collection methods (curbside/drop-off) and separation methods (source-/post-separation). In the Netherlands, the collection routes of plastic waste are the same as those of
Spatial econometrics models for congestion prediction with in-vehicle route guidance
Hu, J.; Kaparias, I.; Bell, M. G. H.
2009-01-01
This study explores the congestion dependence relationship among links using microsimulation, based on data from a real road network. The work is motivated by recent innovations to improve the reliability of Dynamic Route Guidance (DRG) systems. The reliability of DRG systems can be significantly enhanced by adding a function to predict the congestion in the road network. This paper also talks about the application of spatial econometrics modelling to congestion prediction, by using historica...
Vann, Robert E.; Wise, Laura E.; Varvel, Stephen A.; Philibin, Scott D.; Walentiny, D. Matthew; Porter, Joseph H.
2009-01-01
Replacement therapy with the synthetic μ-opioid agonist methadone is an efficacious treatment for opioid abuse. While much is known about methadone’s pharmacology, its discriminative stimulus properties remain largely unexplored. The present study sought to establish methadone discrimination in rats. Moreover, some research suggests that route of administration alters the discriminative stimulus of methadone. Thus, the present study also compared intraperitoneal (i.p.) and subcutaneous (s.c.)...
Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong
2015-01-01
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404
Jisheng Zhang
2015-06-01
Full Text Available It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks.
Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong
2015-01-01
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs' route planning for small and medium-scale networks. PMID:26076404
A Time-Slotted On-Demand Routing Protocol for Mobile Ad Hoc Unmanned Vehicle Systems
Hope Forsmann; Robert Hiromoto; John Svoboda
2007-04-01
The popularity of UAVs has increased dramatically because of their successful deployment in military operations, their ability to preserve human life, and the continual improvements in wireless communication that serves to increase their capabilities. We believe the usefulness of UAVs would be dramatically increased if formation flight were added to the list of capabilities. Currently, sustained formation flight with a cluster of UAVs has only been achieved with two nodes by the Multi-UAV Testbed at the Massachusetts Institute of Technology. (Park, 2004) Formation flight is a complex operation requiring the ability to adjust the flight patterns on the fly and correct for wind gusts, terrain, and differences in node equipment. All of which increases the amount of inner node communication. Since one of the problems with MANET communication is network congestion, we believe a first step towards formation flight can be made through improved inner node communication. We have investigated current communication routing protocols and developed an altered hybrid routing protocol in order to provide communication with less network congestion.
Minimum Makespan Multi-vehicle Dial-a-Ride
Gørtz, Inge Li; Nagarajan, Viswanath; Ravi, R.
-vehicle Dial-a-Ride problem, there are q vehicles each having capacity k and where each vehicle j is an element of [q] has its own depot-vertex r(j) is an element of V. A feasible schedule consists of a capacitated route for each vehicle (where vehicle j originates and ends at its depot r(j)) that together...... move all objects from their sources to destinations. The objective is to find a feasible schedule that minimizes the maximum completion time (i.e. makespan) of vehicles, where the completion time of vehicle j is the time when it returns to its depot r(j) at the end of its route. We consider the...
Asynchronous successive approximation register (SAR) analog-to-digital converters (ADC) feature high energy efficiency but medium performance. From the point of view of speed, the key bottleneck is the unit capacitor size. In this paper, a small size three-dimensional (3-D) metal—oxide—metal (MOM) capacitor is proposed. The unit capacitor has a capacitance of 1-fF. It shapes as an umbrella, which is designed for fast settling consideration. A comparison among the proposed capacitor with other 3-D MOM capacitors is also given in the paper. To demonstrate the effectiveness of the MOM capacitor, a 6-b capacitive DAC is implemented in TSMC 1P9M 65 nm LP CMOS technology. The DAC consumes a power dissipation of 0.16 mW at the rate of 100 MS/s, excluding a source-follower based output buffer. Static measurement result shows that INL is less than ±1 LSB and DNL is less than ±0.5 LSB. In addition, a 100 MS/s 9-bit SAR ADC with the proposed 3-D capacitor is simulated. (paper)
Chixiao, Chen; Jixuan, Xiang; Huabin, Chen; Jun, Xu; Fan, Ye; Ning, Li; Junyan, Ren
2015-05-01
Asynchronous successive approximation register (SAR) analog-to-digital converters (ADC) feature high energy efficiency but medium performance. From the point of view of speed, the key bottleneck is the unit capacitor size. In this paper, a small size three-dimensional (3-D) metal—oxide—metal (MOM) capacitor is proposed. The unit capacitor has a capacitance of 1-fF. It shapes as an umbrella, which is designed for fast settling consideration. A comparison among the proposed capacitor with other 3-D MOM capacitors is also given in the paper. To demonstrate the effectiveness of the MOM capacitor, a 6-b capacitive DAC is implemented in TSMC 1P9M 65 nm LP CMOS technology. The DAC consumes a power dissipation of 0.16 mW at the rate of 100 MS/s, excluding a source-follower based output buffer. Static measurement result shows that INL is less than ±1 LSB and DNL is less than ±0.5 LSB. In addition, a 100 MS/s 9-bit SAR ADC with the proposed 3-D capacitor is simulated.
Routing and scheduling problems
Reinhardt, Line Blander
to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...
Kim Oanh, N. T.; Kongpran, J.; Hang, N. T.; Parkpian, P.; Hung, N. T. Q.; Lee, S.-B.; Bae, G.-N.
2013-10-01
Traffic is a major source of air pollution in urban areas of developing countries that leads to high exposure risk of urban dwellers. This study comparatively investigated levels of fine particles (PM2.5), SO2, NO2, and BTEX (benzene, toluene, ethylbenzene and xylenes) at fixed roadsides and on traveling routes in congested urban and less congested suburban areas of Bangkok in 2010. The roadside air quality monitoring was done at two opposite sites across the selected roads. The traffic counting was made simultaneously in these roads and hourly flows of 8 different vehicle types were determined. Roadside PM2.5 levels during dry season were high in both the city center and suburban area, significantly above the wet season, with 65-75% measurements exceeded 24 h Thailand ambient air quality standard of 50 μg m-3. Oppositely, roadside BTEX levels measured in the city center during wet season were higher than dry season and well above those in suburban area. Diurnal variations and the results of SPSS (Statistical Package for the Social Sciences) analysis showed associations between roadside pollutants levels and hourly traffic flows. The differences in pollution levels between 2 monitoring sites across a road were explained by road configurations and prevalent wind directions. On-route pollution levels were measured simultaneously both inside and outside selected vehicles (van, pickup), and on motorcycle. The on-route PM2.5 levels along the urban route were higher during the dry season than wet season. PM2.5 levels inside the vehicles were lower than outside whereas the opposite was observed for BTEX. BTEX were higher on more congested urban sub-routes with lower vehicle speeds. Higher pollution levels suggest a high risk of exposure.
Gad, Shayne Cox; Spainhour, Charles B; Shoemake, Catherine; Pallman, Danielle R Stackhouse; Stricker-Krongrad, Alain; Downing, Philip A; Seals, Richard E; Eagle, Leslie Anne; Polhamus, Kara; Daly, Jennifer
2016-03-01
Formulation of nonclinical evaluations is a challenge, with the fundamental need to achieve multiples of the clinical exposure complicated by differences in species and routes of administration-specific tolerances, depending on concentrations, volumes, dosing regimen, duration of each administration, and study duration. Current practice to approach these differences is based on individual experience and scattered literature with no comprehensive data source (the most notable exception being our 2006 publication on this same subject). Lack of formulation tolerance data results in excessive animal use, unplanned delays in the evaluation and development of drugs, and vehicle-dependent results. A consulting firm, a chemical company, and 4 contract research organizations conducted a rigorous data mining operation of vehicle data from studies dating from 1991 to 2015, enhancing the data from this author's 2006 publication (3 of the six 2015 contributors were also 2006 contributors). Additional data were found in the published literature. The results identified 108 single-component vehicles (and 305 combination formulations) used in more than 1,040 studies across multiple species (dog, primate, rat, mouse, rabbit, guinea pig, minipig, pig, chick embryo, and cat) by multiple routes for a wide range of study durations. The tabulated data include maximum tolerated use levels by species, route, duration of study, dose-limiting toxicity where reported, review of the available literature on each vehicle, guidance on syringe selection, volume and pH limits by route with basic guidance on nonclinical formulation development, and guidance on factors to be considered in nonclinical route selection. PMID:26755718
Perusek, Gail P. (Inventor)
2003-01-01
The present invention provides for measurements of the principal strain magnitudes and directions, and maximum shear strain that occurs in a porous specimen, such as plastic, ceramic or porous metal, when it is loaded (or subjected to a load). In one embodiment the invention includes a capacitive delta extensometer arranged with six sensors in a three piece configuration, with each sensor of each pair spaced apart from each other by a predetermined angle, such as 120 degrees.
A algorithm for the Vehicle Problem
Aziz Ezzatneshan
2010-09-01
Full Text Available In this paper, we propose a hybrid ACO algorithm for solving vehicle routing problem (VRP heuristically in combination with an exact In the basic VRP, geographically scattered customers of known demand are supplied from a single depot by a fleet of identically capacitated vehicles. The intuition of the proposed algorithm is that nodes which are near to each other will probably belong to the same branch of the minimum spanning tree of the problem graph and thus will probably belong to the same route in VRP. Given a clustering of client nodes, the solution is to find a route in these clusters by using ACO with a modified version of transition rule of the ants. At the end of each iteration, ACO tries to improve the quality of solutions by using a local search algorithm, and update the associated weights of the graph arcs.
Study on vehicle routing problem based on heuristic ant colony optimization%基于启发式蚁群算法的VRP问题研究
刘晓勇; 付辉
2011-01-01
When Ant Colony Optimization algorithm (ACO) is applied to vehicle routing problem, it always spends much time and has worse solutions.This paper uses ACO based on a heuristic method for vehicle routing problem.This heuristic method combines distance matrix with saving route matrix to assign initial pheromone matrix.Three benchmark datasets are chosen to verify performance of the new algorithm. Experiments show that ant colony optimization based on heuristic information has better solution and spends less time.%针对蚁群算法求解VRP问题时收敛速度慢,求解质量不高的缺点,把城市和仓库间的距离矩阵和路径节约矩阵信息融入到初始信息素矩阵中作为启发式信息引入到蚁群算法中用于求解有容量限制的车辆路径规划问题(CVRP),在三个基准数据集上的实验研究表明,基于启发式信息的蚁群算法与基本蚁群算法相比能够以较快的速度收敛到较好的解.
Raja, Umar Waqas; Mustafa, Bilal
2010-01-01
Vehicular Ad Hoc Network (VANET) is a sub class of mobile ad hoc networks. VANET provides wireless communication among vehicles and vehicle to road side equipments. The communication between vehicles is used for safety, comfort and for entertainment as well. The performance of communication depends on how better the routing takes place in the network. Routing of data depends on the routing protocols being used in network. In this study we investigated about different ad hoc routing protocols ...
Imine, Hocine; LABORATOIRE CENTRAL DES PONTS ET CHAUSSEES - LCPC
2009-01-01
RAPPORT DE CONTRAT The aim of this report is to develop models to be used to estimate HGV impact on infrastructures (road and bridge). Vehicle characteristics and road data will be used as inputs to infrastructure behaviour models and simulation software to calculate load effects, in order to estimate and reduce the risks of infrastructure damage. Data will also be used to improve the understanding of the pavement deterioration process and optimise the maintenance operations. Traffic load ...
ALEKSA, Michael; BLERVAQUE, Vincent; CEREZO, Veronique; DELEFOSSE, Rémi; DOLCEMASCOLO, Victor; EICHLOM, Claudia; Ihs, Anita; SJOGREN, Leif; SPIELHOFER, Roland; STUTZ, Rainer
2007-01-01
RAPPORT DE CONTRAT The main purpose of this report is to summarise the results of work package 1 System conception and User Requirements to a system architecture for the HeavyRoute project. This summary shall offer a structural basis for the other technical work packages, especially for work package 3 and work package 4. Work package 1 was dedicated to develop the system conception of HeavyRoute and to gather and analyse the user requirements for an intelligent routing, guidance and naviga...
基于ACS-GA算法的车辆路径问题研究%An ACS-GA Hybrid Optimization Method to Solve Vehicle Routing Problem
赵婉忻; 曲仕茹
2011-01-01
Vehicle routing problem is an important research area in intelligent transportation and business logistics. Planning the vehicle routes reasonably, reducing the delivery mileage and minimizing the cost of logistic distribution are great significance to increase economic efficiency. The paper focuses on vehicle routing problem with time windows in logistic distribution and establishes an improved mathematical model in which the delivery time and delivery distance is shortest. A novel hybrid optimization method integrating ant colony system with genetic algorithm ( ACS - GA) is presented. The initial solution is obtained by ant colony system. A genetic algorithm is used to improve the performance of ACS by reproduction, crossover and mutation operations. The ACS - GA hybrid optimization method can overcome the premature phenomenon and enhance the global search ability. Based on the benchmark datasets of vehicle routing problem with time windows, the experimental results demonstrate that the proposed method has a better ability to search the global optimal solution than other optimization methods.%物流配送车辆路径问题是智能交通和商业物流领域中一个重要研究方面.合理规划车辆的行驶路线,减少配送里程,降低物流成本,对提高经济效益具有重要意义.重点分析了带时间窗的物流配送车辆路径问题,建立了兼顾配送时间与配送距离最短的改进数学模型.提出了基于蚁群系统算法和遗传算法相融合的混合算法.该算法利用蚁群系统算法得到初始解,运用遗传算法中复制、交叉、变异操作对解的种群多样性进行扩充,克服了蚁群系统算法的早熟现象,增强了算法的全局搜索能力.基于标准数据集的实验结果表明,该算法与其他优化方法相比较,具有较好的搜索车辆路径最优解的能力.
Research of Vehicle Routing Problem Based on Fuzzy Time Windows%基于模糊时间窗的车辆调度问题研究
王旭坪; 张凯; 胡祥培
2011-01-01
An increasing number of enterprises are focusing on the vehicle routing problems (VRP) because of expanded logistics support. VRP belongs to typical NP-Hard problems. An enterprise typically spends 25% to 30% of total expenses on vehicle routing problems because they can affect economic efficiency and customer benefits. Therefore, it is important to research VRP and optimize logistics activities.Exiting literature has focused on the vehicle routing problem with hard time and soft time windows. In the VRP with hard time window, the service time must fall within each customer' s time window. Due to the limitation of hard time window and the number of available vehicles, it is often unable to find feasible schedules. To deal with issues pertaining to the violation of time window, researchers have proposed the concept of "soft time window". In the VRP with soft time window, a penalty cost is added once a time window is violated, and the penalty cost is often assumed to be linear with the degree of violation. In some cases, violation of time window does not directly incur any penalty cost, although the satisfaction levels of customers may drop and lead to benefit loss in the long term. In many realistic applications, the hard time window or soft time window does represent customer requirements very well. Under these circumstances, the fuzzy processing of time window can reflect customers' requirements well and truly. Until now, few studies have addressed VRP-with fuzzy time window when the number of vehicle is limited. There are many real-life situations where the number of vehicle is limited, such as logistics distribution, post express and so on. Thus, this paper proposes and solves vehicle routing problems based on the fuzzy time window and a definite number of vehicles. In this paper, a fuzzy membership function is used to characterize customers' satisfaction levels by analyzing customers' practical requirements of the service time window.A multi-objective model
基于模糊期望值模型的车辆路径问题%Vehicle routing problem based on fuzzy expected value model
王连锋; 宋建社; 杨正磊; 曹继平
2012-01-01
Aiming at the vehicle routing problem with fuzzy demands, the probability of vehicle service failure was analyzed based on fuzzy credibility theory, and a fuzzy expected value model was formulated. A parallel particle swarm optimization with double layers tabu search was proposed for routes optimization. In this algorithm, two different types of tabu search space were inserted, and two neighborhood arithmetic operators were designed by using new iterative formula and roulette strategy. The effectiveness of proposed method was verified by simulation contrast tests.%针对模糊需求的车辆路径问题，基于模糊可信性理论对车辆服务失败事件进行可能性分析，建立了一个模糊期望值模型，提出一种带双层禁忌搜索的并行粒子群算法。该算法引入两种不同的禁忌空间，采用新的粒子迭代公式，并利用轮盘赌策略设计了两类邻域算子。通过仿真对比实验表明了该算法的有效性。
Hoesel, van Lodewijk; Tüysüz-Erman, Aysegul; Havinga, P.J.M.; Brogle, Marc; Heijenk, Geert; Braun, Torsten; Konstantas, Dimitri
2009-01-01
In wireless sensor network (WSN) applications with multiple gateways, it is key to route location dependent subscriptions efficiently at two levels in the system. At the gateway level, data sinks must not waste the energy of the WSN by injecting subscriptions that are not relevant for the nodes in t
False capacitance of supercapacitors
Ragoisha, G. A.; Aniskevich, Y. M.
2016-01-01
Capacitance measurements from cyclic voltammetry, galvanostatic chronopotentiometry and calculation of capacitance from imaginary part of impedance are widely used in investigations of supercapacitors. The methods assume the supercapacitor is a capacitor, while real objects correspond to different equivalent electric circuits and show various contributions of non-capacitive currents to the current which is used for calculation of capacitance. Specific capacitances which are presented in F g-1...
VANET Routing Protocols: Pros and Cons
Paul, Bijan; Ibrahim, Md.; Bikas, Md. Abu Naser
2012-01-01
VANET (Vehicular Ad-hoc Network) is a new technology which has taken enormous attention in the recent years. Due to rapid topology changing and frequent disconnection makes it difficult to design an efficient routing protocol for routing data among vehicles, called V2V or vehicle to vehicle communication and vehicle to road side infrastructure, called V2I. The existing routing protocols for VANET are not efficient to meet every traffic scenarios. Thus design of an efficient routing protocol h...
Research on the Algorithm for 3L-CVRP with Considering the Utilization Rate of Vehicles
Ma, Han-Wu; Zhu, Wei; Xu, Sen
Integrated optimization of vehicle routing problem and container loading problem has become a research hotspot in current logistics distribution. Firstly, a mathematical model of the three-dimensional loading capacitated vehicle routing problem (3L-CVRP) is made out under the assumption of which the delivered items are rectangular, considering the rotation of items, last in first out (LIFO) rule and the loading of fragile items which are all in accordance with the realistic conditions, and the objective is to minimize the total driving distance and maximize the utilization rate of vehicle. Then, in order to solve this problem, this paper divides the process of routing and loading into two levels, and a new algorithm which combined Tabu Search (TS) with Local Search (LS) is presented. At last, the feasibility and effectiveness of the method and algorithm is proved by the adoption example.
Conductive two-dimensional titanium carbide 'clay' with high volumetric capacitance.
Ghidiu, Michael; Lukatskaya, Maria R; Zhao, Meng-Qiang; Gogotsi, Yury; Barsoum, Michel W
2014-12-01
Safe and powerful energy storage devices are becoming increasingly important. Charging times of seconds to minutes, with power densities exceeding those of batteries, can in principle be provided by electrochemical capacitors--in particular, pseudocapacitors. Recent research has focused mainly on improving the gravimetric performance of the electrodes of such systems, but for portable electronics and vehicles volume is at a premium. The best volumetric capacitances of carbon-based electrodes are around 300 farads per cubic centimetre; hydrated ruthenium oxide can reach capacitances of 1,000 to 1,500 farads per cubic centimetre with great cyclability, but only in thin films. Recently, electrodes made of two-dimensional titanium carbide (Ti3C2, a member of the 'MXene' family), produced by etching aluminium from titanium aluminium carbide (Ti3AlC2, a 'MAX' phase) in concentrated hydrofluoric acid, have been shown to have volumetric capacitances of over 300 farads per cubic centimetre. Here we report a method of producing this material using a solution of lithium fluoride and hydrochloric acid. The resulting hydrophilic material swells in volume when hydrated, and can be shaped like clay and dried into a highly conductive solid or rolled into films tens of micrometres thick. Additive-free films of this titanium carbide 'clay' have volumetric capacitances of up to 900 farads per cubic centimetre, with excellent cyclability and rate performances. This capacitance is almost twice that of our previous report, and our synthetic method also offers a much faster route to film production as well as the avoidance of handling hazardous concentrated hydrofluoric acid. PMID:25470044
Conductive two-dimensional titanium carbide `clay' with high volumetric capacitance
Ghidiu, Michael; Lukatskaya, Maria R.; Zhao, Meng-Qiang; Gogotsi, Yury; Barsoum, Michel W.
2014-12-01
Safe and powerful energy storage devices are becoming increasingly important. Charging times of seconds to minutes, with power densities exceeding those of batteries, can in principle be provided by electrochemical capacitors--in particular, pseudocapacitors. Recent research has focused mainly on improving the gravimetric performance of the electrodes of such systems, but for portable electronics and vehicles volume is at a premium. The best volumetric capacitances of carbon-based electrodes are around 300 farads per cubic centimetre; hydrated ruthenium oxide can reach capacitances of 1,000 to 1,500 farads per cubic centimetre with great cyclability, but only in thin films. Recently, electrodes made of two-dimensional titanium carbide (Ti3C2, a member of the `MXene' family), produced by etching aluminium from titanium aluminium carbide (Ti3AlC2, a `MAX' phase) in concentrated hydrofluoric acid, have been shown to have volumetric capacitances of over 300 farads per cubic centimetre. Here we report a method of producing this material using a solution of lithium fluoride and hydrochloric acid. The resulting hydrophilic material swells in volume when hydrated, and can be shaped like clay and dried into a highly conductive solid or rolled into films tens of micrometres thick. Additive-free films of this titanium carbide `clay' have volumetric capacitances of up to 900 farads per cubic centimetre, with excellent cyclability and rate performances. This capacitance is almost twice that of our previous report, and our synthetic method also offers a much faster route to film production as well as the avoidance of handling hazardous concentrated hydrofluoric acid.
Mesoscopic Capacitance Oscillations
Buttiker, Markus; Nigg, Simon
2006-01-01
We examine oscillations as a function of Fermi energy in the capacitance of a mesoscopic cavity connected via a single quantum channel to a metallic contact and capacitively coupled to a back gate. The oscillations depend on the distribution of single levels in the cavity, the interaction strength and the transmission probability through the quantum channel. We use a Hartree-Fock approach to exclude self-interaction. The sample specific capacitance oscillations are in marked contrast to the c...
Unmanned Aerial Vehicle Route Planning for Traffic Information Collection%面向交通信息采集的无人飞机路径规划
刘晓锋; 彭仲仁; 张立业; 李立
2012-01-01
引入无人飞机作为城市道路固定交通检测设备的辅助手段,部署无人飞机进行道路交通信息采集,提出了无人飞机的路径规划问题.考虑了无人飞机数量有限,不足以对所有目标进行侦察的情形,建立了以总巡航距离最短、巡航目标数量最多的多目标优化模型,提出了可行路径的重组方法,构造了求解该问题的非支配排序遗传算法.案例分析结果表明:构造的算法可以求出无人飞机路径规划的近似最优解,与最优初始可行解相比,总巡航距离减少了13.07％,巡航目标数量增加了41.67％.最后,讨论了无人飞机在道路交通信息采集中可能面临的问题.%In this paper, the unmanned aerial vehicle (UAV) route planning problem is introduced to deploy the UAV for road traffic information collection. The scenario of using limited UAVs to detect road sections is considered, and a multi-objective optimization model is developed, which uses the number of the UAVs and UAV maximum cruise distance as constraints and aims to minimize the total cruise distance and maximize the number of detected road sections. A novel non-dominated sorting genetic algorithm for this problem is then proposed. The case study shows that the nearly optimal solution for planning UAV routes can be acquired effectively. Compared the obtained solution with the optimal feasible solution, the total cruise distance is reduced by 13.07% and the number of detected targets is increased by 41.67%. Finally, some issues on deploying UAVs for traffic information collection are discussed.
Variable Synthetic Capacitance
Kleinberg, L. L.
1986-01-01
Feedback amplifier circuit synthesizes electronically variable capacitance. Variable Synthetic Capacitor is amplifier circuit with follower/feedback configuration. Effective input capacitance depends on input set current. If synthetic capacitor is connected across resonant element of oscillator, oscillator frequency controlled via input set current. Circuit especially suitable for fine frequency adjustments of piezoelectric-crystal or inductor/capacitor resonant oscillators.
VANET Routing Protocols: Pros and Cons
Paul, Bijan; Bikas, Md Abu Naser
2012-01-01
VANET (Vehicular Ad-hoc Network) is a new technology which has taken enormous attention in the recent years. Due to rapid topology changing and frequent disconnection makes it difficult to design an efficient routing protocol for routing data among vehicles, called V2V or vehicle to vehicle communication and vehicle to road side infrastructure, called V2I. The existing routing protocols for VANET are not efficient to meet every traffic scenarios. Thus design of an efficient routing protocol has taken significant attention. So, it is very necessary to identify the pros and cons of routing protocols which can be used for further improvement or development of any new routing protocol. This paper presents the pros and cons of VANET routing protocols for inter vehicle communication.
... Alternative fuels Advanced gas and diesel vehicles Explaining EVs and PHEVs Hydrogen fuel cell vehicles GHG emissions ... gas emissions Routes to a lower GHG transportation future What if: Ideas for reducing transportation GHG We' ...
Research on the Vehicle Route Planning Determined by Quantity Demand%需求量确定的车辆线路规划研究
葛长飞
2014-01-01
Recently, the logistics industry is rapidly developed. The cost effectiveness has become the focus of enterprises. Transportation cost is an important factor that affects the logistics costs. The existing vehicle route planning researches lack a consideration of the demand, which makes it difficult to adapt to actual demand change. This paper optimizes the existing BRP basic model in the aspect of demand, establishes the function model deter-mined by demand, uses LINGO software to solve, and studies the numerical example, verifies the model, reason-ably plans and designs the business lines and reduce the logistics costs, which is of a theoretical reference value.%近几年，物流业发展迅猛，成本效益已成为企业关注的焦点，运输成本是影响物流成本的重要因素。现有的车辆线路规划研究中，缺少对需求量因素的考虑，难以适应需求量变动的实际情况。本文在需求量方面对现有VRP基本模型进行优化，建立需求量确定的函数模型，运用LINGO软件进行求解，再进行算例分析，对模型进行验证。这对企业进行科学的线路规划设计，降低物流成本，具有重要的理论参考意义。
殷招伟; 戴文博; 钱俊彦
2015-01-01
The interdisciplinary application of intelligent transportation system comes into being just to meet people’s growing demand.The analysis of shortest path is the key problem in the application of VRGS (Vehicle Route Guidance System), the Dijkstra algorithm is the common algorithm to solve this problem effectively. Combined two-tree Dijkstra algorithm and multi-core and multi-threading technology, this paper optimizes and improves the traditional Dijkstra algorithm. And it discusses the application of the algorithm in VRGS.At last, this paper poves its practicality and efficiency by simulating the shortest path search process of Guilin.%为了满足人们日益增长的出行需求，跨学科的智能交通系统应运而生。最短路径分析是GIS车辆诱导系统应用的关键问题，Dijkstra 算法是解决该问题的常用算法。文章结合二树 Dijkstra 算法的思想和现代多核多线程的技术，对 Dijkstra算法进行了优化与改进，并对该算法在车辆诱导系统中的应用进行了探讨。该系统以桂林市为例模拟了最短路径搜过程，证明该算法的高效性和实用性。
刘云龙; 印玺
2015-01-01
为解决城市轨道车辆生产线存在的生产效率不高与稳定性差等问题，提出了一种基于有向加权网络的城市轨道车辆工艺路线优化方法。该方法首先利用有向加权网络理论构建车辆生产线的生产网络模型，然后以生产线可靠性与制造成本为目标，建立轨道车辆工艺路线的多目标优化模型，并基于粒子群算法得到最优工艺路线生成算法，最后以某轨道列车生产线为例进行了验证，结果表明，该方法能显著降低生产线的生产成本，提高生产线的生产效率与稳定性。%The process route optimization of rail vehicle production is a complicated problem.It proposes a direct-ed weighted network to establish the complex processing relationships among working stations, takes the manufac-turing cost and the reliability of the rail vehicle production route as object.In order to improve the reliability of production route, it builds an optimization model combining the reliability of the production route and manufac-turing cost, designs particle swarm algorithm for the optimal process route generation.The results prove the effec-tive of the optimization method.
System for Measuring Capacitance
McNichol, Randal S. (Inventor)
2001-01-01
A system has been developed for detecting the level of a liquid in a tank wherein a capacitor positioned in the tank has spaced plates which are positioned such that the dielectric between the plates will be either air or the liquid, depending on the depth of the liquid in the tank. An oscillator supplies a sine wave current to the capacitor and a coaxial cable connects the capacitor to a measuring circuit outside the tank. If the cable is very long or the capacitance to be measured is low, the capacitance inherent in the coaxial cable will prevent an accurate reading. To avoid this problem, an inductor is connected across the cable to form with the capacitance of the cable a parallel resonant circuit. The impedance of the parallel resonant circuit is infinite, so that attenuation of the measurement signal by the stray cable capacitance is avoided.
Eaton, William P.; Staple, Bevan D.; Smith, James H.
2000-01-01
A microelectromechanical (MEM) capacitance pressure sensor integrated with electronic circuitry on a common substrate and a method for forming such a device are disclosed. The MEM capacitance pressure sensor includes a capacitance pressure sensor formed at least partially in a cavity etched below the surface of a silicon substrate and adjacent circuitry (CMOS, BiCMOS, or bipolar circuitry) formed on the substrate. By forming the capacitance pressure sensor in the cavity, the substrate can be planarized (e.g. by chemical-mechanical polishing) so that a standard set of integrated circuit processing steps can be used to form the electronic circuitry (e.g. using an aluminum or aluminum-alloy interconnect metallization).
Manginell, Ronald P; Moorman, Matthew W; Wheeler, David R
2014-05-27
A microfabricated capacitive chemical sensor can be used as an autonomous chemical sensor or as an analyte-sensitive chemical preconcentrator in a larger microanalytical system. The capacitive chemical sensor detects changes in sensing film dielectric properties, such as the dielectric constant, conductivity, or dimensionality. These changes result from the interaction of a target analyte with the sensing film. This capability provides a low-power, self-heating chemical sensor suitable for remote and unattended sensing applications. The capacitive chemical sensor also enables a smart, analyte-sensitive chemical preconcentrator. After sorption of the sample by the sensing film, the film can be rapidly heated to release the sample for further analysis. Therefore, the capacitive chemical sensor can optimize the sample collection time prior to release to enable the rapid and accurate analysis of analytes by a microanalytical system.
Induced Charge Capacitive Deionization
Rubin, S.; Suss, M. E.; Biesheuvel, P. M.; Bercovici, M.
2016-01-01
We demonstrate the phenomenon of induced-charge capacitive deionization (ICCDI) that occurs around a porous and conducting particle immersed in an electrolyte, under the action of an external electrostatic field. The external electric field induces an electric dipole in the porous particle, leading to capacitive charging of its volume by both cations and anions at opposite poles. This regime is characterized both by a large RC charging time and a small electrochemical charge relaxation time, ...
Wang, B; Zhao, X; Guo, H; Wang, J.
1999-01-01
We analyze the nonlinear voltage dependence of electrochemical capacitance for nanoscale conductors. This voltage dependence is due to the finite density of states of the conductors. Within Hartree theory we derive an exact expression for the electrochemical capacitance–voltage curve for a parallel plate system. The result suggests a quantum scanning capacitance microscopy at the nanoscale: by inverting the capacitance–voltage expression one is able to deduce the local spectral function of th...
Quantum capacitance: a microscopic derivation
Mukherjee, Sreemoyee; MANNINEN, M; Deo, P. Singha
2010-01-01
We start from microscopic approach to many body physics and show the analytical steps and approximations required to arrive at the concept of quantum capacitance. These approximations are valid only in the semi-classical limit and the quantum capacitance in that case is determined by Lindhard function. The effective capacitance is the geometrical capacitance and the quantum capacitance in series, and this too is established starting from a microscopic theory.
High bandwidth on-chip capacitive tuning of microtoroid resonators.
Baker, Christopher G; Bekker, Christiaan; McAuslan, David L; Sheridan, Eoin; Bowen, Warwick P
2016-09-01
We report on the design, fabrication and characterization of silica microtoroid based cavity opto-electromechanical systems (COEMS). Electrodes patterned onto the microtoroid resonators allow for rapid capacitive tuning of the optical whispering gallery mode resonances while maintaining their ultrahigh quality factor, enabling applications such as efficient radio to optical frequency conversion, optical routing and switching applications. PMID:27607646
High bandwidth on-chip capacitive tuning of microtoroid resonators
Baker, Christopher G; McAuslan, David L; Sheridan, Eoin; Bowen, Warwick P
2016-01-01
We report on the design, fabrication and characterization of silica microtoroid based cavity opto-electromechanical systems (COEMS). Electrodes patterned onto the microtoroid resonators allow for rapid capacitive tuning of the optical whispering gallery mode resonances while maintaining their ultrahigh quality factor, enabling applications such as efficient radio to optical frequency conversion, optical routing and switching applications.
Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.
2015-06-01
The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.
Enhanced ant colony optimization for inventory routing problem
Wong, Lily; Moin, Noor Hasnah
2015-10-01
The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.
Membrane capacitive deionization
Biesheuvel, P.M.; Wal, van der A.
2010-01-01
Membrane capacitive deionization (MCDI) is an ion-removal process based on applying an electrical potential difference across an aqueous solution which flows in between oppositely placed porous electrodes, in front of which ion-exchange membranes are positioned. Due to the applied potential, ions ar
Steerable Capacitive Proximity Sensor
Jenstrom, Del T.; Mcconnell, Robert L.
1994-01-01
Steerable capacitive proximity sensor of "capaciflector" type based partly on sensing units described in GSC-13377 and GSC-13475. Position of maximum sensitivity adjusted without moving sensor. Voltage of each driven shield adjusted separately to concentrate sensing electric field more toward one side or other.
Optimal Routing of Cigarette Delivery Vehicle Based on Genetic Algorithm%基于遗传算法的烟草配送车路径优化问题
叶安新
2011-01-01
On the basis of establishing an optimized model for optimal routing of cigarette delivery vehicle problem, the paper uses techniques such as roulette wheel selection, partially matched crossover and self adaptation for fitness function, designs a genotic algorithm based on natural numbers. At the end of the paper make some experimental calculations using this algorithm. The experimental calculations results demonstrate that the optimal or nearly optimal solutions to the Cigarette Delivery Vehicle routing problem can be easily obtained by using genetic algorithm.%在建立烟草配送车路径优化问题模型的基础上,采用轮盘赌复制法、部分匹配交叉算法、和适应度函数自适应调整等技术,设计了基于自然数编码的遗传算法,最后以这种方法进行了实验计算,通过计算结果表明,用遗传算法进行烟草车配送路径优化,可以方便有效地求得问题的最优解或近似最优解.
陈小双; 翟为刚; 赵万里
2011-01-01
Presents a route planning for Unmanned Aerial Vehicles （UAV） based on the Particle Swarm Optimization（PSO）. Introduces the PSO to establish a single-object UAV route planning on the equivalent digital map. And analyses the PSO in details. The simulation experiment result demonstrates that this method can complete planning mission efficiently and obtain a desirable three-dimensional route.%提出一种基于粒子群优化算法的无人机航迹规划方法，利用粒子群优化算法，在等效数字地图中实现单个目标点的无人机航迹规划，并对算法性能进行仔细分析，仿真结果表明，该方法能够快速有效地完成航迹规划任务．得到满意的三维航迹。
Induced Charge Capacitive Deionization
Rubin, S; Biesheuvel, P M; Bercovici, M
2016-01-01
We demonstrate the phenomenon of induced-charge capacitive deionization (ICCDI) that occurs around a porous and conducting particle immersed in an electrolyte, under the action of an external electrostatic field. The external electric field induces an electric dipole in the porous particle, leading to capacitive charging of its volume by both cations and anions at opposite poles. This regime is characterized both by a large RC charging time and a small electrochemical charge relaxation time, which leads to rapid and significant deionization of ionic species from a volume which is on the scale of the particle. We show by theory and experiment that the transient response around a cylindrical particle results in spatially non-uniform charging and non-steady growth of depletion regions which emerge around the particle's poles. Potentially, ICCDI can be useful in applications where fast concentration changes of ionic species are required over large volumes.
Molecular Aspects of Capacitation
Gulfidan Zulfikaroglu; Hulya Ozgur; Sait Polaturkey
2010-01-01
Male and female gamets are derived from the primordial germ cells, which migrate from the wall of the yolk sac toward the developing gonads. Following a series of mitotic divisions these cells increase in number at the gonads. The primordial germ cells differentiate into spermatogonia and take the form of mature spermatozoa after spermotogensis and spermotogenesis at puberty. Capacitation is the reaction, which includes all of the molecular and physiological events of mature sperm to gain the...
Capacitance of graphene nanoribbons
Shylau, A. A.; Klos, J. W.; Zozoulenko, I. V.
2009-01-01
We present an analytical theory for the gate electrostatics and the classical and quantum capacitance of the graphene nanoribbons (GNRs) and compare it with the exact self-consistent numerical calculations based on the tight-binding p-orbital Hamiltonian within the Hartree approximation. We demonstrate that the analytical theory is in a good qualitative (and in some aspects quantitative) agreement with the exact calculations. There are however some important discrepancies. In order to underst...
Electrical capacitance clearanceometer
Hester, Norbert J. (Inventor); Hornbeck, Charles E. (Inventor); Young, Joseph C. (Inventor)
1992-01-01
A hot gas turbine engine capacitive probe clearanceometer is employed to measure the clearance gap or distance between blade tips on a rotor wheel and its confining casing under operating conditions. A braze sealed tip of the probe carries a capacitor electrode which is electrically connected to an electrical inductor within the probe which is inserted into a turbine casing to position its electrode at the inner surface of the casing. Electrical power is supplied through a voltage controlled variable frequency oscillator having a tuned circuit in which the probe is a component. The oscillator signal is modulated by a change in electrical capacitance between the probe electrode and a passing blade tip surface while an automatic feedback correction circuit corrects oscillator signal drift. A change in distance between a blade tip and the probe electrode is a change in capacitance therebetween which frequency modulates the oscillator signal. The modulated oscillator signal which is then processed through a phase detector and related circuitry to provide an electrical signal is proportional to the clearance gap.
求解带时间窗车辆路径问题的混合智能算法%Hybrid intelligent algorithm for vehicle routing problem with time windows
孙小军
2015-01-01
Based on cuckoo search algorithm and partheno-genetic algorithm,a hybrid intelligent algorithm is designed to solve the vehicle routing problem with time windows.Firstly,this algorithm analyzes the locations of customers by clustering method,and then,forms the optimal route for the divided areas.This hybrid intelligent algorithm not only improves the operation of the cuckoo search algorithm,which is to randomly change the whole location of the cuckoo nest when the cuckoo eggs are found by the nest's master,but also accelerates the search speed of optimal delivery route by using partheno-genetic algorithm.In addition,the computational complexities of this hybrid intelligent algorithm and cuckoo search algorithm are analyzed and compared.Finally,according to test results under ISO standard test collection-Benchmark Problems,it is verified that this hybrid intelligent algorithm is an effective method in solving the vehicle routing problem with time windows.%基于布谷鸟搜索算法和单亲遗传算法，设计了一种求解带时间窗车辆路径问题的混合智能算法。该算法首先对客户位置进行聚类分析，然后再进行各区域的路径优化。混合智能算法不仅改进了布谷鸟搜索算法中当鸟卵被鸟窝主人发现后需要随机改变整个鸟窝位置的操作，同时引入的单亲遗传算法加快了最优配送路线的搜索速度。分析和比较了混合智能算法与布谷鸟搜索算法的计算复杂度。最后采用国际通用标准测试集 Benchmark Problems 进行测试。结果显示，混合智能算法是求解带时间窗车辆路径问题的一种有效算法。