Search results for "routing"

showing 10 items of 587 documents

An ILS-Based Metaheuristic for the Stacker Crane Problem

2012

[EN] In this paper we propose a metaheuristic algorithm for the Stacker Crane Problem. This is an NP-hard arc routing problem whose name derives from the practical problem of operating a crane. Here we present a formulation and a lower bound for this problem and propose a metaheuristic algorithm based on the combination of a Multi-start and an Iterated Local Search procedures. Computational results on a large set of instances are presented.

Mathematical optimizationIterated local searchComputer scienceStackerComputerApplications_COMPUTERSINOTHERSYSTEMSMetaheuristicsUpper and lower boundsParallel metaheuristicDirected rural postman problemCombinatorial OptimizationCombinatorial optimizationLarge set (combinatorics)MATEMATICA APLICADAMetaheuristicArc routingAlgorithm
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An Iterative Method for Pricing American Options Under Jump-Diffusion Models

2011

We propose an iterative method for pricing American options under jump-diffusion models. A finite difference discretization is performed on the partial integro-differential equation, and the American option pricing problem is formulated as a linear complementarity problem (LCP). Jump-diffusion models include an integral term, which causes the resulting system to be dense. We propose an iteration to solve the LCPs efficiently and prove its convergence. Numerical examples with Kou's and Merton's jump-diffusion models show that the resulting iteration converges rapidly.

Mathematical optimizationIterative methodValuation of optionsJump diffusionConvergence (routing)Finite difference methodFinite difference methods for option pricingLinear complementarity problemTerm (time)MathematicsSSRN Electronic Journal
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The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality

2016

The fundamental phenomenon that has been used to enhance the convergence speed of learning automata (LA) is that of incorporating the running maximum likelihood (ML) estimates of the action reward probabilities into the probability updating rules for selecting the actions. The frontiers of this field have been recently expanded by replacing the ML estimates with their corresponding Bayesian counterparts that incorporate the properties of the conjugate priors. These constitute the Bayesian pursuit algorithm (BPA), and the discretized Bayesian pursuit algorithm. Although these algorithms have been designed and efficiently implemented, and are, arguably, the fastest and most accurate LA report…

Mathematical optimizationLearning automataDiscretizationbusiness.industryBayesian probability02 engineering and technologyMathematical proof01 natural sciencesConjugate priorField (computer science)010104 statistics & probabilityArtificial IntelligenceConvergence (routing)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligence0101 mathematicsbusinessBeta distributionMathematics
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Lower and upper bounds for the mixed capacitated arc routing problem

2006

This paper presents a linear formulation, valid inequalities, and a lower bounding procedure for the mixed capacitated arc routing problem (MCARP). Moreover, three constructive heuristics and a memetic algorithm are described. Lower and upper bounds have been compared on two sets of randomly generated instances. Computational results show that the average gaps between lower and upper bounds are 0.51% and 0.33%, respectively.

Mathematical optimizationLower boundGeneral Computer Science0211 other engineering and technologiesMixed graphHeuristic02 engineering and technologyManagement Science and Operations ResearchUpper and lower boundsBounding overwatchMixed graph0502 economics and businessCapacitated arc routing problemConstructive heuristicMathematics050210 logistics & transportation021103 operations researchWaste collectionHeuristic05 social sciencesMemetic algorithm[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Cutting plane[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModeling and SimulationMemetic algorithmArc routingCutting-plane method
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Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

2015

Abstract Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important ( factor prioritisation ) and non-influential ( factor fixing ) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality–quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiar…

Mathematical optimizationMathematical modelSettore ICAR/03 - Ingegneria Sanitaria-AmbientaleUncertaintyContrast (statistics)Numerical method6. Clean waterTerm (time)law.inventionSystems analysisMathematical modelMathematical models; Numerical methods; Sewer sediments; Systems analysis; Uncertainty; Urban drainage modelling; Water Science and TechnologySystems analysilawSewer sedimentConvergence (routing)StatisticsVenn diagramSensitivity (control systems)Urban drainage modellingReliability (statistics)MathematicsWater Science and Technology
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Stochastic dynamics of linear elastic trusses in presence of structural uncertainties (virtual distortion approach)

2004

Structures involving uncertainties in material and/or in geometrical parameters are referred to as uncertain structures. Reliability analysis of such structures strongly depends on variation of parameters and probabilistic approach is often used to characterize structural uncertainties. In this paper dynamic analysis of linearly elastic system in presence of random parameter variations will be performed. In detail parameter fluctuations have been considered as inelastic, stress and parameter dependent superimposed strains. Analysis is then carried out via superposition principle accounting for response to external agencies and parameter dependent strains. Proposed method yields asymptotic s…

Mathematical optimizationMechanical EngineeringLinear elasticityAerospace EngineeringTrussOcean EngineeringStatistical and Nonlinear PhysicsCondensed Matter PhysicsVariation of parametersDynamic load testingSuperposition principleVirtual DistortionNuclear Energy and EngineeringDynamic AnalysiSuperposition PrincipleDistortionStochastic ParameterConvergence (routing)Statistical physicsAsymptotic expansionCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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A multi-objective strategy for concurrent mapping and routing in networks on chip

2009

The design flow of network-on-chip (NoCs) include several key issues. Among other parameters, the decision of where cores have to be topologically mapped and also the routing algorithm represent two highly correlated design problems that must be carefully solved for any given application in order to optimize several different performance metrics. The strong correlation between the different parameters often makes that the optimization of a given performance metric has a negative effect on a different performance metric. In this paper we propose a new strategy that simultaneously refines the mapping and the routing function to determine the Pareto optimal configurations which optimize averag…

Mathematical optimizationNetwork on a chipRobustness (computer science)Computer scienceMultipath routingAlgorithm designFault toleranceNetwork topologyMulti-objective optimization2009 IEEE International Symposium on Parallel & Distributed Processing
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A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems

2013

The unequal area facility layout problem (UA-FLP) comprises a class of extremely difficult and widely applicable optimization problems arising in diverse areas and meeting the requirements for real-world applications. Genetic Algorithms (GAs) have recently proven their effectiveness in finding (sub) optimal solutions to many NP-hard problems such as UA-FLP. A main issue in such approach is related to the genetic encoding and to the evolutionary mechanism implemented, which must allow the efficient exploration of a wide solution space, preserving the feasibility of the solutions and ensuring the convergence towards the optimum. In addition, in realistic situations where several design issues…

Mathematical optimizationOptimization problemGeneral EngineeringSolution setPareto principleMulti Objective Genetic Algorithm electre method unequal area facility layout problemsComputer Science ApplicationsRankingArtificial IntelligenceGenetic algorithmConvergence (routing)ELECTRESelection (genetic algorithm)MathematicsExpert Systems with Applications
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Using a TSP heuristic for routing order pickers in warehouses

2010

In this paper, we deal with the sequencing and routing problem of order pickers in conventional multi-parallel-aisle warehouse systems. For this NP-hard Steiner travelling salesman problem (TSP), exact algorithms only exist for warehouses with at most three cross aisles, while for other warehouse types literature provides a selection of dedicated construction heuristics. We evaluate to what extent reformulating and solving the problem as a classical TSP leads to performance improvements compared to existing dedicated heuristics. We report average savings in route distance of up to 47% when using the LKH (Lin-Kernighan-Helsgaun) TSP heuristic. Additionally, we examine if combining problem-sp…

Mathematical optimizationOrder pickingInformation Systems and ManagementGeneral Computer ScienceEconomicsOrder pickingLogisticsManagement Science and Operations ResearchAisleSteiner tree problemTravelling salesman problemIndustrial and Manufacturing Engineeringsymbols.namesakeLocal search (optimization)WarehousingMathematicsRoutingComputer. AutomationHeuristicbusiness.industryModeling and SimulationsymbolsRouting (electronic design automation)HeuristicsbusinessMathematicsofComputing_DISCRETEMATHEMATICSorder picking routing warehousing logistics
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The multiple vehicle pickup and delivery problem with LIFO constraints

2015

Abstract This paper approaches a pickup and delivery problem with multiple vehicles in which LIFO conditions are imposed when performing loading and unloading operations and the route durations cannot exceed a given limit. We propose two mixed integer formulations of this problem and a heuristic procedure that uses tabu search in a multi-start framework. The first formulation is a compact one, that is, the number of variables and constraints is polynomial in the number of requests, while the second one contains an exponential number of constraints and is used as the basis of a branch-and-cut algorithm. The performances of the proposed solution methods are evaluated through an extensive comp…

Mathematical optimizationPolynomialInformation Systems and ManagementGeneral Computer ScienceManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringTabu searchFIFO and LIFO accountingModeling and SimulationVehicle routing problemBenchmark (computing)Integer programmingAlgorithmBranch and cutInteger (computer science)MathematicsEuropean Journal of Operational Research
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