Search results for "routing"

showing 10 items of 587 documents

A branch-and-cut algorithm for the Orienteering Arc Routing Problem

2016

[EN] In arc routing problems, customers are located on arcs, and routes of minimum cost have to be identified. In the Orienteering Arc Routing Problem (OARP),in addition to a set of regular customers that have to be serviced, a set of potential customers is available. From this latter set, customers have to be chosen on the basis of an associated profit. The objective is to find a route servicing the customers which maximize the total profit collected while satisfying a given time limit on the route.In this paper, we describe large families of facet-inducing inequalities for the OARP and present a branch-and-cut algorithm for its solution. The exact algorithm embeds a procedure which builds…

Mathematical optimization021103 operations researchGeneral Computer Science0211 other engineering and technologiesOrienteering02 engineering and technologyManagement Science and Operations ResearchTime limitRouting problems with profitsPolyhedronExact algorithmOrienteering Arc Routing ProblemBranch-and-cutModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingDestination-Sequenced Distance Vector routingMATEMATICA APLICADAInteger programmingArc routingAlgorithmBranch and cutMathematicsComputers & Operations Research
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Bidirectional labeling in column-generation algorithms for pickup-and-delivery problems

2018

Abstract For the exact solution of many types of vehicle-routing problems, column-generation based algorithms have become predominant. The column-generation subproblems are then variants of the shortest-path problem with resource constraints which can be solved well with dynamic-programming labeling algorithms. For vehicle-routing problems with a pickup-and-delivery structure, the strongest known dominance between two labels requires the delivery triangle inequality (DTI) for reduced costs to hold. When the direction of labeling is altered from forward labeling to backward labeling, the DTI requirement becomes the pickup triangle inequality (PTI). DTI and PTI cannot be guaranteed at the sam…

Mathematical optimization021103 operations researchInformation Systems and ManagementGeneral Computer ScienceTriangle inequalityComputation0211 other engineering and technologiesStructure (category theory)02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringAccelerationModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPickupPoint (geometry)Column generationRouting (electronic design automation)AlgorithmMathematicsEuropean Journal of Operational Research
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A fast heuristic for solving the D1EC coloring problem

2010

In this paper we propose an efficient heuristic for solving the Distance-1 Edge Coloring problem (D1EC) for the on-the-fly assignment of orthogonal wireless channels in wireless as soon as a topology change occurs. The coloring algorithm exploits the simulated annealing paradigm, i.e., a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a sub optimal coloring scheme even for the case of dynamic channel allocation. However, a stateful implementation of the D1EC scheme is needed in order to speed-up the network coloring upon topology changes. In fact, a stateful D1EC reduces the algorithm’s convergen…

Mathematical optimization:QA Mathematics::QA75 Electronic computers. Computer science [Q Science]TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESChannel allocation schemesHeuristic (computer science)Computer scienceSettore ING-INF/03 - Telecomunicazioni:T Technology (General) [T Technology]Topology (electrical circuits)Greedy coloringEdge coloringTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESStateful firewall:Q Science (General) [Q Science]TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYConvergence (routing)Simulated annealing:TK Electrical engineering. Electronics Nuclear engineering [T Technology]Channel assignment Edge coloring Simulated annealing.MathematicsofComputing_DISCRETEMATHEMATICS
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Algorithms for Rational Discrete Least Squares Approximation Part I: Unconstrained Optimization

1976

In this paper a modification of L. Wittmeyer’s method ([1], [14]) for rational discrete least squares approximation is given which corrects for its failure to converge to a non-optimal point in general. The modification makes necessary very little additional computing effort only. It is analysed thoroughly with respect to its conditions for convergence and its numerical properties. A suitable implementation is shown to be benign in the sense of F. L. Bauer [2]. The algorithm has proven successful even in adverse situations.

Mathematical optimizationComputer scienceNon-linear least squaresDiscrete optimizationConvergence (routing)Point (geometry)Quadratic unconstrained binary optimizationUnconstrained optimizationTotal least squaresAlgorithmLeast squares
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Direct Numerical Methods for Optimal Control Problems

2003

Development of interior point methods for linear and quadratic programming problems occurred during the 1990’s. Because of their simplicity and their convergence properties, interior point methods are attractive solvers for such problems. Moreover, extensions have been made to more general convex programming problems.

Mathematical optimizationComputer scienceNumerical analysisConjugate gradient methodConvergence (routing)Convex optimizationMathematicsofComputing_NUMERICALANALYSISPositive-definite matrixQuadratic programmingOptimal controlInterior point method
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A Simple Metaheuristic for the FleetSize and Mix Problem with TimeWindows

2017

This paper presents a powerful new single-parameter metaheuristic to solve the Fleet Size and Mix Vehicle Routing Problem with Time Windows. The key idea of the new metaheuristic is to perform a random number of random-sized jumps in random order through four well-known local search operators. Computational testing on the 600 large-scale benchmarks of Bräysy et al. (Expert Syst Appl 36(4):8460–8475, 2009) show that the new metaheuristic outperforms previous best approaches, finding 533 new best-known solutions. Despite the significant number of random components, it is demonstrated that the variance of the results is rather low. Moreover, the suggested metaheuristic is shown to scale almost…

Mathematical optimizationComputer scienceSimple (abstract algebra)business.industryVehicle routing problemKey (cryptography)Scale (descriptive set theory)Local search (optimization)Variance (accounting)businessMetaheuristicParallel metaheuristic
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A powerful route minimization heuristic for the vehicle routing problem with time windows

2009

We suggest an efficient route minimization heuristic for the vehicle routing problem with time windows. The heuristic is based on the ejection pool, powerful insertion and guided local search strategies. Experimental results on the Gehring and Homberger's benchmarks demonstrate that our algorithm outperforms previous approaches and found 18 new best-known solutions.

Mathematical optimizationComputer scienceTime windowsApplied MathematicsVehicle routing problemGuided Local SearchMinificationManagement Science and Operations ResearchHeuristicsAlgorithmIndustrial and Manufacturing EngineeringSoftwareOperations Research Letters
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Vehicle Routing Problem with Time Windows, Part II: Metaheuristics

2005

This paper surveys the research on the metaheuristics for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval; all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Metaheuristics are general solution procedures that explore the solution space to identify good solutions and often embed some of the standard route construction and improvemen…

Mathematical optimizationComputer scienceVehicle routing problemGenetic algorithmBenchmark (computing)TransportationInterval (mathematics)Routing (electronic design automation)HeuristicsMetaheuristicTabu searchCivil and Structural EngineeringTransportation Science
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Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms

2005

This paper presents a survey of the research on the vehicle routing problem with time windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval, all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Both traditional heuristic route construction methods and recent local search algorithms are examined. The basic features of each method are described, and experimental results for Solom…

Mathematical optimizationComputer sciencebusiness.industryHeuristic (computer science)TransportationTabu searchGenetic algorithmVehicle routing problemBenchmark (computing)Local search (optimization)Routing (electronic design automation)businessAlgorithmMetaheuristicCivil and Structural EngineeringTransportation Science
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Performance modeling of epidemic routing

2006

In this paper, we develop a rigorous, unified framework based on ordinary differential equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study of Markovian models is quite complex and numerical solution impractical for large networks, the corresponding ODE models yield closed-form expressions for several performance metrics of interest, and a numerical solution complexity that does not increase with the number of nodes. Using this ODE approach, we investigate how resources such as buffer space and the number of copies made for a packet can be tra…

Mathematical optimizationComputingMethodologies_SIMULATIONANDMODELINGComputer Networks and CommunicationsDifferential equationComputer scienceWireless ad hoc networkNetwork packetNumerical analysisMathematicsofComputing_NUMERICALANALYSISOdeMarkov processMarkov modelsymbols.namesakeOrdinary differential equationMetric (mathematics)symbolsRouting (electronic design automation)ScalingSimulation
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