Search results for " algorithms"

showing 10 items of 612 documents

A tabu search algorithm for large-scale guillotine (un)constrained two-dimensional cutting problems

2002

Abstract In this paper we develop several heuristic algorithms for the two-dimensional cutting problem (TDC) in which a single stock sheet has to be cut into a set of small pieces, while maximising the value of the pieces cut. They can be considered to be general purpose algorithms because they solve the four versions of the TDC: weighted and unweighted, constrained and unconstrained. We begin by proposing two constructive procedures based on simple bounds obtained by solving one-dimensional knapsack problems. We then use these constructive algorithms as building blocks for more complex procedures. We have developed a greedy randomised adaptive search procedure (GRASP) which is very fast an…

Mathematical optimizationGeneral Computer ScienceGRASPSearch procedureManagement Science and Operations ResearchConstructiveTabu searchCutting stock problemKnapsack problemModeling and SimulationConstructive algorithmsHeuristicsAlgorithmMathematicsComputers & Operations Research
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On the approximability of the range assignment problem on radio networks in presence of selfish agents

2005

AbstractWe consider the range assignment problem in ad-hoc wireless networks in the context of selfish agents: A network manager aims to assigning transmission ranges to the stations in order to achieve strong connectivity of the network within a minimal overall power consumption. Station is not directly controlled by the manager and may refuse to transmit with a certain transmission range because it might be costly in terms of power consumption.We investigate the existence of payment schemes which induce the stations to follow the decisions of a network manager in computing a range assignment, that is, truthful mechanisms for the range assignment problem. We provide both positive and negat…

Mathematical optimizationGeneral Computer ScienceSettore INF/01 - Informaticabusiness.industryWireless networkApproximation algorithmContext (language use)Approximation algorithmsTheoretical Computer ScienceNetwork managementAlgorithmic mechanism design; Energy consumption in wireless networks; Approximation algorithmsEnergy consumption in wireless networksalgorithmic mechanism design; approximation algorithms; energy consumption in wireless networksbusinessTime complexityAssignment problemAlgorithmConnectivityAlgorithmic mechanism designAlgorithmic mechanism designMathematicsComputer Science(all)Theoretical Computer Science
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The distributed assembly permutation flowshop scheduling problem

2013

Nowadays, improving the management of complex supply chains is a key to become competitive in the twenty-first century global market. Supply chains are composed of multi-plant facilities that must be coordinated and synchronised to cut waste and lead times. This paper proposes a Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP) with two stages to model and study complex supply chains. This problem is a generalisation of the Distributed Permutation Flowshop Scheduling Problem (DPFSP). The first stage of the DAPFSP is composed of f identical production factories. Each one is a flowshop that produces jobs to be assembled into final products in a second assembly stage. The o…

Mathematical optimizationJob shop schedulingStrategy and ManagementSupply chainESTADISTICA E INVESTIGACION OPERATIVANeighbourhood (graph theory)Management Science and Operations ResearchIndustrial and Manufacturing EngineeringDistributed assembly flowshopVariable neighborhood descentVariable (computer science)PermutationConstructive algorithmsKey (cryptography)ORGANIZACION DE EMPRESASProduction (computer science)Mathematics
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Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping

2013

This paper addresses the Network-on-Chip (NoC) application mapping problem. This is an NP-hard problem that deals with the optimal topological placement of Intellectual Property cores onto the NoC tiles. Network-on-Chip application mapping Evolutionary Algorithms are developed, evaluated and optimized for minimizing the NoC communication energy. Two crossover and one mutation operators are proposed. It is analyzed how each optimization algorithm performs with every genetic operator, in terms of solution quality and convergence speed. Our proposed operators are compared with state-of-the-art genetic operators for permutation problems. Finally, the problem is approached in a multi-objective w…

Mathematical optimizationMutation operatorTheoretical computer scienceComputer Networks and CommunicationsComputer scienceQuality control and genetic algorithmsCrossoverEvolutionary algorithmGenetic operatorMulti-objective optimizationNetwork on a chipArtificial IntelligenceHardware and ArchitectureSimulated annealingGenetic algorithmGenetic representationSoftwareMicroprocessors and Microsystems
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Some Aspects Regarding the Application of the Ant Colony Meta-heuristic to Scheduling Problems

2010

Scheduling is one of the most complex problems that appear in various fields of activity, from industry to scientific research, and have a special place among the optimization problems In our paper we present the results of our computational study i.e an Ant Colony Optimization algorithm for the Resource-Constrained Project Scheduling Problem that uses dynamic pheromone evaporation.

Mathematical optimizationOptimization problemComputer scienceNurse scheduling problemAnt colony optimization algorithmsMeta heuristicAnt colonyComputingMethodologies_ARTIFICIALINTELLIGENCEMembrane computingMetaheuristicScheduling (computing)
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Memetic Algorithms in Engineering and Design

2012

When dealing with real-world applications, one often faces non-linear and nondifferentiable optimization problems which do not allow the employment of exact methods. In addition, as highlighted in [104], popular local search methods (e.g. Hooke-Jeeves, Nelder Mead and Rosenbrock) can be ill-suited when the real-world problem is characterized by a complex and highly multi-modal fitness landscape since they tend to converge to local optima. In these situations, population based meta-heuristics can be a reasonable choice, since they have a good potential in detecting high quality solutions. For these reasons, meta-heuristics, such as Genetic Algorithms (GAs), Evolution Strategy (ES), Particle …

Mathematical optimizationOptimization problemLocal optimumbusiness.industryComputer scienceAnt colony optimization algorithmsMathematicsofComputing_NUMERICALANALYSISParticle swarm optimizationMemetic algorithmLocal search (optimization)businessEvolution strategyTabu search
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An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GA

2015

In this paper, we describe an interactive evolutionary algorithm called Interactive WASF-GA to solve multiobjective optimization problems. This algorithm is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In Interactive WASF-GA, a decision maker (DM) provides preference information at each iteration simple as a reference point consisting of desirable objective function values and the number of solutions to be compared. Using this information, the desired number of solutions are generated to represent the region of interest of the Pareto optimal front associated to the reference point given. Interactive WASF-GA implies a much lower computational…

Mathematical optimizationOptimization problemMultiobjective programmingComputer scienceEvolutionary algorithmReference point approachInteractive evolutionary computationPareto optimal solutionsEvolutionary algorithmsPreference (economics)AlgorithmMulti-objective optimizationInteractive methods
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Experiments on a Prey Predators System

2003

The paper describes a prey-predators system devoted to perform experiments on concurrent complex environment. The problem has be treated as an optimization problem. The prey goal is to escape from the predators reaching its lair, while predators want to capture the prey. At the end of the 19th century, Pareto found an optimal solutions for decision problems regarding more than one criterion at the same time. In most cases this ‘Pareto-set’ cannot be determined analytically or the computation time could be exponential. In such cases, evolutionary Algorithms (EA) are powerful optimization tools capable of finding optimal solutions of multi-modal problems. Here, both prey and predators learn i…

Mathematical optimizationOptimization problemSettore INF/01 - InformaticaComputer scienceComputationGenetic Algorithms Path finding obstacle avoidanceEvolutionary algorithmPareto principleDecision problemSet (psychology)ComputingMethodologies_ARTIFICIALINTELLIGENCEField (computer science)Predation
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Handling precedence constraints in scheduling problems by the sequence pair representation

2015

In this paper, we show that sequence pair (SP) representation, primarily applied to the rectangle packing problems appearing in the VLSI industry, can be a solution representation of precedence constrained scheduling. We present three interpretations of sequence pair, which differ in complexity of schedule evaluation and size of a corresponding solution space. For each interpretation we construct an incremental precedence constrained SP neighborhood evaluation algorithm, computing feasibility of each solution in the insert neighborhood in an amortized constant time per examined solution, and prove the connectivity property of the considered neighborhoods. To compare proposed interpretations…

Mathematical optimizationPrecedence diagram methodControl and Optimizationrectangle packing problemMultiprocessing0102 computer and information sciences02 engineering and technology01 natural sciencesScheduling (computing)0202 electrical engineering electronic engineering information engineeringDiscrete Mathematics and CombinatoricsschedulingComputer Science::Operating SystemsMathematicsVery-large-scale integrationAmortized analysisApplied MathematicsJob scheduling problemComputer Science ApplicationsComputational Theory and Mathematics010201 computation theory & mathematicsMetaheuristic algorithmsTheory of computation020201 artificial intelligence & image processingAlgorithmprecedence constraintssequence pairJournal of Combinatorial Optimization
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Multiobjective ant colony search algorithm optimal electrical distribution system planning

2005

A dynamic multiobjective, MO, algorithm based on the ant colony search, the multiobjective ant colony search algorithm, MOACS, is presented. The application domain is that of dynamic planning for electrical distribution systems. A time horizon of H years has been considered during which the distribution system are modified according to the new internal (loads) and external (market, reliability, power quality) requirements. In this scenario, the objectives the Authors consider most important for utilities in strategical planning are: the quality requirement connected to the decrease of the expected number of interruptions per year and customer, in the considered time frame, and the choice fo…

Mathematical optimizationSearch algorithmComputer scienceReliability (computer networking)Ant colony optimization algorithmsmedia_common.quotation_subjectMathematicsofComputing_NUMERICALANALYSISPareto principleQuality (business)Time horizonAnt colonyComputingMethodologies_ARTIFICIALINTELLIGENCEmedia_commonProceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)
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