Showing papers on "Vehicle routing problem published in 2014"
Book•
05 Dec 2014
TL;DR: The text of the new edition is either completely new or significantly revised and provides extensive and complete state-of-the-art coverage of vehicle routing by those who have done most of the innovative research in the area.
Abstract: Vehicle routing problems, among the most studied in combinatorial optimization, arise in many practical contexts (freight distribution and collection, transportation, garbage collection, newspaper delivery, etc.). Operations researchers have made significant developments in the algorithms for their solution, and Vehicle Routing: Problems, Methods, and Applications, Second Edition reflects these advances. The text of the new edition is either completely new or significantly revised and provides extensive and complete state-of-the-art coverage of vehicle routing by those who have done most of the innovative research in the area; it emphasizes methodology related to specific classes of vehicle routing problems and, since vehicle routing is used as a benchmark for all new solution techniques, contains a complete overview of current solutions to combinatorial optimization problems. It also includes several chapters on important and emerging applications, such as disaster relief and green vehicle routing. Audience: This book is intended for both researchers and graduate level students in operations research and applied mathematics. Practitioners will find this book particularly useful. Readers need a basic knowledge of the main methods for the solution of combinatorial optimization problems.
756 citations
TL;DR: The purpose is to review the most up-to-date state-of-the-art of GVRP, discuss how the traditional VRP variants can interact with G VRP and offer an insight into the next wave of research into GVRp.
Abstract: Green Logistics has emerged as the new agenda item in supply chain management. The traditional objective of distribution management has been upgraded to minimizing system-wide costs related to economic and environmental issues. Reflecting the environmental sensitivity of vehicle routing problems (VRP), an extensive literature review of Green Vehicle Routing Problems (GVRP) is presented. We provide a classification of GVRP that categorizes GVRP into Green-VRP, Pollution Routing Problem, VRP in Reverse Logistics, and suggest research gaps between its state and richer models describing the complexity in real-world cases. The purpose is to review the most up-to-date state-of-the-art of GVRP, discuss how the traditional VRP variants can interact with GVRP and offer an insight into the next wave of research into GVRP. It is hoped that OR/MS researchers together with logistics practitioners can be inspired and cooperate to contribute to a sustainable industry.
741 citations
TL;DR: This work introduces the electric vehicle-routing problem with time windows and recharging stations E-VRPTW and presents a hybrid heuristic that combines a variable neighborhood search algorithm with a tabu search heuristic, which incorporates the possibility of recharging at any of the available stations using an appropriate recharging scheme.
Abstract: Driven by new laws and regulations concerning the emission of greenhouse gases, carriers are starting to use electric vehicles for last-mile deliveries. The limited battery capacities of these vehicles necessitate visits to recharging stations during delivery tours of industry-typical length, which have to be considered in the route planning to avoid inefficient vehicle routes with long detours. We introduce the electric vehicle-routing problem with time windows and recharging stations E-VRPTW, which incorporates the possibility of recharging at any of the available stations using an appropriate recharging scheme. Furthermore, we consider limited vehicle freight capacities as well as customer time windows, which are the most important constraints in real-world logistics applications. As a solution method, we present a hybrid heuristic that combines a variable neighborhood search algorithm with a tabu search heuristic. Tests performed on newly designed instances for the E-VRPTW as well as on benchmark instances of related problems demonstrate the high performance of the heuristic proposed as well as the positive effect of the hybridization.
695 citations
TL;DR: This paper analyzes the recent literature on the standard LRP and new extensions such as several distribution echelons, multiple objectives or uncertain data and results of state-of-the-art metaheuristics are compared on standard sets of instances for the classical LRP, the two-echelon L RP and the truck and trailer problem.
545 citations
TL;DR: A comprehensive review of inventory-routing problem literature is provided, based on a new classification of the problem, which categorizes IRPs with respect to their structural variants and the availability of information on customer demand.
Abstract: The inventory-routing problem (IRP) dates back 30 years. It can be described as the combination of vehicle-routing and inventory management problems, in which a supplier has to deliver products to a number of geographically dispersed customers, subject to side constraints. It provides integrated logistics solutions by simultaneously optimizing inventory management, vehicle routing, and delivery scheduling. Some exact algorithms and several powerful metaheuristic and matheuristic approaches have been developed for this class of problems, especially in recent years. The purpose of this article is to provide a comprehensive review of this literature, based on a new classification of the problem. We categorize IRPs with respect to their structural variants and the availability of information on customer demand.
522 citations
TL;DR: An adaptive large neighborhood search algorithm (ALNS), combined with a speed optimization procedure, to solve the bi-objective PRP and shows that HM is highly effective in finding good-quality non-dominated solutions on PRP instances with 100 nodes.
363 citations
TL;DR: In this article, the authors present several heuristics for a variation of the vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need for recharge during their duties.
Abstract: This paper presents several heuristics for a variation of the vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need for recharge during their duties. In addition to the routing plan, the amount of energy recharged and the technology used must also be determined. Constructive and local search heuristics are proposed, which are exploited within a non deterministic Simulated Annealing framework. Extensive computational results on varying instances are reported, evaluating the performance of the proposed algorithms and analyzing the distinctive elements of the problem (size, geographical configuration, recharge stations, autonomy, technologies, etc.).
359 citations
TL;DR: The proposed Unified Hybrid Genetic Search metaheuristic relies on problem-independent unified local search, genetic operators, and advanced diversity management methods and shows remarkable performance, which matches or outperforms the current state-of-the-art problem-tailored algorithms.
328 citations
01 Jan 2014
307 citations
TL;DR: Bike sharing systems offer a mobility service whereby public bicycles, located at different stations across an urban area, are available for shared use and contribute towards obtaining a more sustainable mobility and decreasing traffic and pollution caused by car transportation.
Abstract: Bike sharing systems offer a mobility service whereby public bicycles, located at different stations across an urban area, are available for shared use. These systems contribute towards obtaining a more sustainable mobility and decreasing traffic and pollution caused by car transportation. Since the first bike sharing system was installed in Amsterdam in 1965, the number of such applications has increased remarkably so that hundreds of systems are now operating all over the world. In a bike sharing system, users can take a bicycle from a station, use it to perform a journey and then leave it at a station, not necessarily the same one of departure. This behavior typically leads to a situation in which some stations become full and others are empty. Hence, a balanced system requires the redistribution of bicycles among stations. In this paper, we address the Bike sharing Rebalancing Problem (BRP), in which a fleet of capacitated vehicles is employed in order to re-distribute the bikes with the objective of minimizing total cost. This can be viewed as a special one-commodity pickup-and-delivery capacitated vehicle routing problem. We present four mixed integer linear programming formulations of this problem. It is worth noting that the proposed formulations include an exponential number of constraints, hence, tailor-made branch-and-cut algorithms are developed in order to solve them. The mathematical formulations of the BRP were first computationally tested using data obtained for the city of Reggio Emilia, Italy. Our computational study was then extended to include bike sharing systems from other parts of the world. The information derived from the study was used to build a set of benchmark instances for the BRP which we made publicly available on the web. Extensive experimentation of the branch-and-cut algorithms presented in this paper was carried out and an interesting computational comparison of the proposed mathematical formulations is reported. Finally, several insights on the computational difficulty of the problem are highlighted.
275 citations
TL;DR: This work surveys the state of the art in the field of Vehicle Routing Problem research, summarizing problem combinations, constraints defined, and approaches found and concludes that the Rich VRP arises: combining multiple constraints for tackling realistic problems.
Abstract: The Vehicle Routing Problem (VRP) is a well-known research line in the optimization research community. Its different basic variants have been widely explored in the literature. Even though it has been studied for years, the research around it is still very active. The new tendency is mainly focused on applying this study case to real-life problems. Due to this trend, the Rich VRP arises: combining multiple constraints for tackling realistic problems. Nowadays, some studies have considered specific combinations of real-life constraints to define the emerging Rich VRP scopes. This work surveys the state of the art in the field, summarizing problem combinations, constraints defined, and approaches found.
TL;DR: In this paper, the authors introduced the fleet size and mix pollution-routing problem, which extends the pollution routing problem by considering a heterogeneous vehicle fleet and the main objective is to minimize the sum of vehicle fixed costs and routing cost, where the latter can be defined with respect to the cost of fuel and CO emissions, and driver cost.
Abstract: This paper introduces the fleet size and mix pollution-routing problem which extends the pollution-routing problem by considering a heterogeneous vehicle fleet. The main objective is to minimize the sum of vehicle fixed costs and routing cost, where the latter can be defined with respect to the cost of fuel and CO emissions, and driver cost. Solving this problem poses several methodological challenges. To this end, we have developed a powerful metaheuristic which was successfully applied to a large pool of realistic benchmark instances. Several analyses were conducted to shed light on the trade-offs between various performance indicators, including capacity utilization, fuel and emissions and costs pertaining to vehicle acquisition, fuel consumption and drivers. The analyses also quantify the benefits of using a heterogeneous fleet over a homogeneous one. Full text available at: http://www.sciencedirect.com/science/article/pii/S0191261514001623
01 Feb 2014
TL;DR: The Ant Colony System (ACS) is used to solve the capacitated vehicle routing problem associated with collection of recycling waste from households, treated as nodes in a spatial network and produces high-quality solutions for two-compartment test problems.
Abstract: We demonstrate the use of Ant Colony System (ACS) to solve the capacitated vehicle routing problem associated with collection of recycling waste from households, treated as nodes in a spatial network. For networks where the nodes are concentrated in separate clusters, the use of k-means clustering can greatly improve the efficiency of the solution. The ACS algorithm is extended to model the use of multi-compartment vehicles with kerbside sorting of waste into separate compartments for glass, paper, etc. The algorithm produces high-quality solutions for two-compartment test problems.
27 Aug 2014
TL;DR: A classification in three classes of matheuristics: decomposition approaches, improvement heuristics and branch-and-price/column generation-based approaches is proposed.
Abstract: In this paper, we survey the literature on matheuristics proposed to solve vehicle routing problems. A matheuristic makes use of mathematical programming models in a heuristic framework. Matheuristics have been applied to several different routing problems and include a number of different approaches. We propose a classification in three classes of matheuristics: decomposition approaches, improvement heuristics and branch-and-price/column generation-based approaches. The contribution of this paper is to offer to researchers interested in routing problems a structured overview of the most successful ideas to combine heuristic schemes and mathematical programming models to obtain high quality solutions. Moreover, we analyze the state of the art and provide insights and hints for future research.
TL;DR: A nonlinear integer open location-routing model for relief distribution problem considering travel time, the total cost, and reliability with split delivery is constructed and the non-dominated sorting genetic algorithm and non- dominated sorting differential evolution algorithm are proposed to solve the model.
Abstract: The effective distribution of critical relief in post disaster plays a crucial role in post-earthquake rescue operations. The location of distribution centers and vehicle routing in the available transportation network are two of the most challenging issues in emergency logistics. This paper constructs a nonlinear integer open location-routing model for relief distribution problem considering travel time, the total cost, and reliability with split delivery. It proposes the non-dominated sorting genetic algorithm and non-dominated sorting differential evolution algorithm to solve the proposed model. A case study on the Great Sichuan Earthquake in China expounds the application of the proposed models and algorithms in practice.
TL;DR: The computational results show that the proposed algorithm is competitive against state-of-the-art methods for these two classes of vehicle routing problems, and is able to solve to optimality some previously open instances.
TL;DR: An adaptive large neighborhood search, exploiting the ruin-and-recreate principle, is proposed for solving the vehicle routing problem with multiple routes, and results on Euclidean instances demonstrate the benefits of this multi-level approach.
TL;DR: An efficient implementation of variable neighborhood search that incorporates new features in addition to the adaptation of several existing neighborhoods and local search operators is proposed, including a preprocessing scheme for identifying borderline customers, and a neighborhood reduction test that saves nearly 80% of the CPU time, especially on the large instances.
TL;DR: This paper introduces the Multi-Depot Heterogeneous Dial-A-Ride Problem (MD-H-DARP), a general dial-a-ride problem in which these three real-life aspects may simultaneously be taken into account and a new deterministic annealing meta-heuristic is proposed.
Abstract: Dial-a-ride problems are concerned with the design of efficient vehicle routes for transporting individual persons from specific origin to specific destination locations. In real-life this operational planning problem is often complicated by several factors. Users may have special requirements (e.g. to be transported in a wheelchair) while service providers operate a heterogeneous fleet of vehicles from multiple depots in their service area. In this paper, a general dial-a-ride problem in which these three real-life aspects may simultaneously be taken into account is introduced: the Multi-Depot Heterogeneous Dial-A-Ride Problem (MD-H-DARP). Both a three- and two-index formulation are discussed. A branch-and-cut algorithm for the standard dial-a-ride problem is adapted to exactly solve small problem instances of the MD-H-DARP. To be able to solve larger problem instances, a new deterministic annealing meta-heuristic is proposed. Extensive numerical experiments are presented on different sets of benchmark instances for the homogeneous and the heterogeneous single depot dial-a-ride problem. Instances for the MD-H-DARP are introduced as well. The branch-and-cut algorithm provides considerably better results than an existing algorithm which uses a less compact formulation. All seven previously unsolved benchmark instances for the heterogeneous dial-a-ride problem could be solved to optimality within a matter of seconds. While computation times of the exact algorithm increase drastically with problem size, the proposed meta-heuristic algorithm provides near-optimal solutions within limited computation time for all instances. Several best known solutions for unsolved instances are improved and the algorithm clearly outperforms current state-of-the-art heuristics for the homogeneous and heterogeneous dial-a-ride problem, both in terms of solution quality and computation time.
TL;DR: This work considers the Multi Trip Vehicle Routing Problem, in which a set of geographically scattered customers have to be served by a fleet of vehicles, and aims to minimize the total travel time while respecting temporal and capacity constraints.
TL;DR: This paper develops a solution procedure, in which feasible vehicle routes are constructed via a tabu search algorithm, and proposes a linear programming model to handle the detailed scheduling of customer visits for given routes.
TL;DR: This paper presents a new hybrid variable neighborhood-tabu search heuristic for the Vehicle Routing Problem with Multiple Time windows and proposes a minimum backward time slack algorithm applicable to a multiple time windows environment.
Patent•
14 Mar 2014TL;DR: In this paper, a lane-level vehicle routing and navigation apparatus includes a simulation module that performs microsimulation of individual vehicles in a traffic stream, and a lanelevel optimizer that evaluates conditions along the candidate paths from an origin to a destination as determined by the simulation module, and determines recommended lanelevel maneuvers along candidate paths.
Abstract: A lane-level vehicle routing and navigation apparatus includes a simulation module that performs microsimulation of individual vehicles in a traffic stream, and a lane-level optimizer that evaluates conditions along the candidate paths from an origin to a destination as determined by the simulation module, and determines recommended lane-level maneuvers along the candidate paths. A link-level optimizer may determines the candidate paths based on link travel times determined by the simulation module. The simulation may be based on real-time traffic condition data. Recommended candidate paths may be provided to delivery or service or emergency response vehicles, or used for evacuation planning, or to route vehicles such as garbage or postal trucks, or snowplows. Corresponding methods also may be used for traffic planning and management, including determining, based on microsimulation, at least one of (a) altered road geometry, (b) altered traffic signal settings, such as traffic signal timing, or (c) road pricing.
TL;DR: In this article, a vehicle routing problem with soft time windows and stochastic travel times is studied, where the objective is to minimize the sum of transportation costs and service costs.
TL;DR: In this paper, the authors consider an ordering of customers instead of building a giant tour, and propose an ordering-first split-second approach for vehicle routing. But this approach can be declined for different vehicle routing problems and reviews the associated literature.
Abstract: Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.
TL;DR: A novel multi-objective model is proposed that decouples the minimization of the distribution costs from the maximization ofThe freshness state of the delivered products to examine the relation between distribution scenarios and the cost-freshness trade-off.
TL;DR: This paper provides an exact formulation of the proposed model for the IRP which includes several well-known valid inequalities for some classes of IRPs and proposes three new valid inequalities based on the relation between demand and available capacities.
TL;DR: This paper introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles and designs a hybrid artificial bee colony algorithm designed to solve the EVRP model.
Abstract: The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.
TL;DR: The wide array of circumstances and settings in which the periodic vehicle routing problem has been applied is discussed and the development of solution methods, both exact and heuristic, for the PVRP are described.
Abstract: The periodic vehicle routing problem PVRP first appeared in 1974 in a paper about garbage collection Beltrami and Bodin, Networks 4 1974, 65-74. The wide applicability and versatility of the problem has led to a vast body of literature addressing both novel applications and solution methods. This article discusses the wide array of circumstances and settings in which the PVRP has been applied and describes the development of solution methods, both exact and heuristic, for the PVRP. As with many core research problems, many variants have been proposed. We will describe additional problem variants and extensions, as well as discuss the future of research for the PVRP. © 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 631, 2-15 2014