91 research outputs found

    A matheuristic for the Distance-Constrained Close-Enough Arc Routing Problem

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    [EN] The Close-Enough Arc Routing Problem, also called Generalized Directed Rural Postman Problem, is an arc routing problem with interesting real-life applications, such as routing for meter reading. In this application, a vehicle with a receiver travels through a series of neighborhoods. If the vehicle gets within a certain distance of a meter, the receiver is able to record the gas, water, or electricity consumption. Therefore, the vehicle does not need to traverse every street, but only a few, in order to be close enough to each meter. In this paper we deal with an extension of this problem, the Distance-Constrained Generalized Directed Rural Postman Problem or Distance-Constrained Close Enough Arc Routing Problem, in which a fleet of vehicles is available. The vehicles have to leave from and return to a common vertex, the depot, and the length of their routes must not exceed a maximum distance (or time). For solving this problem we propose a matheuristic that incorporates an effective exact procedure to optimize the routes obtained. Extensive computational experiments have been performed on a set of benchmark instances and the results are compared with those obtained with an exact procedure proposed in the literature.This work was supported by the Spanish Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) through Project MTM2015-68097-P (MINECO/FEDER). Authors want to thank two anonymous referees for their suggestions and comments that have contributed to improve the paper.Corberán, A.; Plana, I.; Reula, M.; Sanchís Llopis, JM. (2019). A matheuristic for the Distance-Constrained Close-Enough Arc Routing Problem. Top. 27(2):312-326. https://doi.org/10.1007/s11750-019-00507-3S312326272Aráoz J, Fernández E, Franquesa C (2017) The generalized arc routing problem. TOP 25:497–525Ávila T, Corberán Á, Plana I, Sanchis JM (2016) A new branch-and-cut algorithm for the generalized directed rural postman problem. Transportation Science 50:750–761Ávila T, Corberán Á, Plana I, Sanchis JM (2017) Formulations and exact algorithms for the distance-constrained generalized directed rural postman problem. EURO Journal on Computational Optimization 5:339–365Cerrone C, Cerulli R, Golden B, Pentangelo R (2017) A flow formulation for the close-enough arc routing problem. In Sforza A. and Sterle C., editors, Optimization and Decision Science: Methodologies and Applications. ODS 2017., volume 217 of Springer Proceedings in Mathematics & Statistics, pages 539–546Corberán Á, Laporte G (editors) (2014) Arc Routing: Problems,Methods, and Applications. MOS-SIAM Series on Optimization,PhiladelphiaCorberán Á, Plana I, Sanchis J.M (2007) Arc routing problems: data instances. http://www.uv.es/~corberan/instancias.htmDrexl M (2007) On some generalized routing problems. PhD thesis, Rheinisch-Westfälische Technische Hochschule, Aachen UniversityDrexl M (2014) On the generalized directed rural postman problem. Journal of the Operational Research Society 65:1143–1154Gendreau M, Laporte G, Semet F (1997) The covering tour problem. Operations Research 45:568–576Hà M-H, Bostel N, Langevin A, Rousseau L-M (2014) Solving the close enough arc routing problem. Networks 63:107–118Mourão MC, Pinto LS (2017) An updated annotated bibliography on arc routing problems. Networks 70:144–194Renaud A, Absi N, Feillet D (2017) The stochastic close-enough arc routing problem. Networks 69:205–221Shuttleworth R, Golden BL, Smith S, Wasil EA (2008) Advances in meter reading: Heuristic solution of the close enough traveling salesman problem over a street network. In: Golden BL, Raghavan S, Wasil EA (eds) The Vehicle Routing Problem: Lastest Advances and New Challenges. Springer, pp 487–50

    Spatial coverage in routing and path planning problems

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    Routing and path planning problems that involve spatial coverage have received increasing attention in recent years in different application areas. Spatial coverage refers to the possibility of considering nodes that are not directly served by a vehicle as visited for the purpose of the objective function or constraints. Despite similarities between the underlying problems, solution approaches have been developed in different disciplines independently, leading to different terminologies and solution techniques. This paper proposes a unified view of the approaches: Based on a formal introduction of the concept of spatial coverage in vehicle routing, it presents a classification scheme for core problem features and summarizes problem variants and solution concepts developed in the domains of operations research and robotics. The connections between these related problem classes offer insights into common underlying structures and open possibilities for developing new applications and algorithms

    Arc routing with trip-balancing and attractiveness measures : A waste collection case study

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    This work focuses on a household (or door to door) waste collection problem in the Portuguese municipality of Seixal, which is modelled as a generalisation of a mixed capacitated arc routing problem (MCARP). The MCARP is known to be NP-hard. The proposed methodology uses: i) a GIS (geographic information system), for input/output and to reduce problem dimensions; ii) a matheuristic that iteratively solves a new hybrid model; and iii) two versions of a two-phase matheuristic. The latter pursues the generation of connected and compacted trips. During the first phase, called initial assignment, some links requiring service are assigned to vehicle services. In the second phase, the hybrid model finishes the assignment and generates a feasible set of trips. The quality of the generated solutions is assessed through the total time, as well as by some attractiveness measures. These measures evaluate the adequacy of the solutions for the real case-study, a crucial aspect for trips that need to be accepted by practitioners. With this purpose, a new attractiveness measure that introduces space dependent penalisation of overlaps, named weighted hull overlap, is also proposed. Computational results with 18 Seixal instances, with 265–1223 nodes and 492–2254 links, point to the good performance of the proposed.info:eu-repo/semantics/publishedVersio

    A Study On The Split Delivery Vehicle Routing Problem

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    This dissertation examines the Split Delivery Vehicle Routing Problem (SDVRP), a relaxed version of classical capacitated vehicle routing problem (CVRP) in which the demand of any client can be split among the vehicles that visit it. We study both scenarios of the SDVRP in this dissertation. For the SDVRP with a fixed number of the vehicles, we provide a Two-Stage algorithm. This approach is a cutting-plane based exact method called Two-Stage algorithm in which the SDVRP is decomposed into two stages of clustering and routing. At the first stage, an assignment problem is solved to obtain some clusters that cover all demand points and get the lower bound for the whole problem; at the second stage, the minimal travel distance of each cluster is calculated as a traditional Traveling Salesman Problem (TSP), and the upper bound is obtained. Adding the information obtained from the second stage as new cuts into the first stage, we solve the first one again. This procedure stops when there are no new cuts to be created from the second stage. Several valid inequalities have been developed for the first stage to increase the computational speed. A valid inequality is developed to completely solve the problem caused by the index of vehicles. Another strong valid inequality is created to provide a valid distance lower bound for each set of demand points. This algorithm can significantly outperform other exact approaches for the SDVRP in the literature. If the number of the vehicles in the SDVRP is a variable, we present a column generation based branch and price algorithm. First, a restricted master problem (RMP) is presented, which is composed of a finite set of feasible routes. Solving the linear relaxation of the RMP, values of dual variables are thus obtained and passed to the sub-problem, the pricing problem, to generate a new column to enter the base of the RMP and solve the new RMP again. This procedure repeats until the objective function value of the pricing problem is greater than or equal to zero (for minimum problem). In order to get the integer feasible (optimal) solution, a branch and bound algorithm is then performed. Since after branching, it is not guaranteed that the possible favorable column will appear in the master problem. Therefore, the column generation is performed again in each node after branching. The computational results indicate this approach is promising in solving the SDVRP in which the number of the vehicles is not fixed

    High-Performance Distributed ML at Scale through Parameter Server Consistency Models

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    As Machine Learning (ML) applications increase in data size and model complexity, practitioners turn to distributed clusters to satisfy the increased computational and memory demands. Unfortunately, effective use of clusters for ML requires considerable expertise in writing distributed code, while highly-abstracted frameworks like Hadoop have not, in practice, approached the performance seen in specialized ML implementations. The recent Parameter Server (PS) paradigm is a middle ground between these extremes, allowing easy conversion of single-machine parallel ML applications into distributed ones, while maintaining high throughput through relaxed "consistency models" that allow inconsistent parameter reads. However, due to insufficient theoretical study, it is not clear which of these consistency models can really ensure correct ML algorithm output; at the same time, there remain many theoretically-motivated but undiscovered opportunities to maximize computational throughput. Motivated by this challenge, we study both the theoretical guarantees and empirical behavior of iterative-convergent ML algorithms in existing PS consistency models. We then use the gleaned insights to improve a consistency model using an "eager" PS communication mechanism, and implement it as a new PS system that enables ML algorithms to reach their solution more quickly.Comment: 19 pages, 2 figure

    A survey on performance analysis of warehouse carousel systems

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    This paper gives an overview of recent research on the performance evaluation and design of carousel systems. We discuss picking strategies for problems involving one carousel, consider the throughput of the system for problems involving two carousels, give an overview of related problems in this area, and present an extensive literature review. Emphasis has been given on future research directions in this area

    A concise guide to existing and emerging vehicle routing problem variants

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    Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges

    Vehicle Routing with Compartments Under Product Incompatibility Constraints

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    This study focuses on a distribution problem involving incompatible products which cannot be stored in a compartment of a vehicle. To satisfy different types of customer demand at minimum logistics cost, the products are stored in different compartments of fleet vehicles, which requires the problem to be modeled as a multiple-compartment vehicle routing problem (MCVRP). While there is an extensive literature on the vehicle routing problem (VRP) and its numerous variants, there are fewer research papers on the MCVRP. Firstly, a novel taxonomic framework for the VRP literature is proposed in this study. Secondly, new mathematical models are proposed for the basic MCVRP, together with its multiple-trip and split-delivery extensions, for obtaining exact solutions for small-size instances. Finally, heuristic algorithms are developed for larger instances of the three problem variants. To test the performance of our heuristics against optimum solutions for larger instances, a lower bounding scheme is also proposed. The results of the computational experiments are reported, indicating validity and a promising performance of an approach
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