Search results for "Multi-objective optimization"

showing 10 items of 192 documents

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
researchProduct

Tangent and Normal Cones in Nonconvex Multiobjective Optimization

2000

Trade-off information is important in multiobjective optimization. It describes the relationships of changes in objective function values. For example, in interactive methods we need information about the local behavior of solutions when looking for improved search directions.

Mathematical optimizationNon-convexityTangentMulti-objective optimizationMathematics
researchProduct

Interactive Method NIMBUS for Nondifferentiable Multiobjective Optimization Problems

1997

An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. The method is capable of handling several nonconvex locally Lipschitzian objective functions subject to nonlinear (possibly nondifferentiable) constraints. The idea of NIMBUS is that the decision maker can easily indicate what kind of improvements are desired and what kind of impairments are tolerable at the point considered. The decision maker is asked to classify the objective functions into five different classes: those to be improved, those to be improved down to some aspiration level, those to be accepted as they are, those to be impaired till some upper bound, and those allowed to …

Mathematical optimizationNonlinear systemMultiobjective optimization problemComputer sciencePoint (geometry)Aspiration levelDecision makerUpper and lower boundsMulti-objective optimization
researchProduct

Non-dominated “trade-off” solutions in television scheduling optimization

2014

The main approaches for the television scheduling design are commonly based on the ratings or revenues maximization objective, and thus, only a single optimal solution can be obtained, corresponding to the best result for the considered objective. Therefore, these approaches lead up to the alternative solutions loss which, even if less effective from the ratings or revenues maximization viewpoint, may be more suitable for the decision maker because of better compromise in relation to factors influencing the decision process. Specifically, such a compromise could be achieved through a suitable “trade-off” between these factors, with reference to the decision context in which the decision mak…

Mathematical optimizationOperations researchRelation (database)Computer scienceStrategy and ManagementCompromisemedia_common.quotation_subjecttelevision scheduling designtelevision scheduling costsScheduling (production processes)integer mathematical programming modelMaximizationManagement Science and Operations ResearchMulti-objective optimizationComputer Science Applicationstelevision ratings forecastmulti-objective optimizationOrder (exchange)Management of Technology and InnovationBusiness and International ManagementSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneInteger (computer science)media_commonCommunication channel
researchProduct

A comparison of different solution approaches to the vehicle scheduling problem in a practical case

2000

Abstract The Vehicle Scheduling Problem (VSP) consists in assigning a set of scheduled trips to a set of vehicles, satisfying a set of constraints and optimizing an objective function. A wide literature exists for the VSP, but usually not all the practical requirements of the real cases are taken into account. In the present paper a practical case is studied, and for it a traditional method is tailored and two innovative heuristics are developed. As the problem presents a multicriteria nature, each of the three algorithms adopts a different approach to multicriteria optimization. Scalarization of the different criteria is performed by the traditional algorithm. A lexicographic approach is f…

Mathematical optimizationOptimization problemGeneral Computer ScienceJob shop schedulingNurse scheduling problemModeling and SimulationGenetic algorithmOperational planningManagement Science and Operations ResearchHeuristicsMulti-objective optimizationAssignment problemMathematics
researchProduct

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
researchProduct

Interactive Multiobjective Optimization of Superstructure SMB Processes

2009

We consider multiobjective optimization problems arising from superstructure formulation of Simulated Moving Bed (SMB) processes. SMBs are widely used in many industrial separations of chemical products and they are challenging from the optimization point of view. We employ efficient interactive multiobjec-tive optimization which enables considering several conflicting objectives simultaneously without unnecessary simplifications as have been done in previous studies. The interactive IND-NIMBUS software combined with the IPOPT optimizer is used to solve multiobjective SMB design problems. The promising results of solving a superstructure SMB optimization problem with four objectives demonst…

Mathematical optimizationOptimization problembusiness.industryComputer scienceInformation and Computer ScienceMulti-objective optimizationchemistry.chemical_compoundSoftwarechemistryConflicting objectivesPoint (geometry)Simulated moving bedbusinessSuperstructure (condensed matter)
researchProduct

Local search based evolutionary multi-objective optimization algorithm for constrained and unconstrained problems

2009

Evolutionary multi-objective optimization algorithms are commonly used to obtain a set of non-dominated solutions for over a decade. Recently, a lot of emphasis have been laid on hybridizing evolutionary algorithms with MCDM and mathematical programming algorithms to yield a computationally efficient and convergent procedure. In this paper, we test an augmented local search based EMO procedure rigorously on a test suite of constrained and unconstrained multi-objective optimization problems. The success of our approach on most of the test problems not only provides confidence but also stresses the importance of hybrid evolutionary algorithms in solving multi-objective optimization problems.

Mathematical optimizationOptimization problembusiness.industryTest functions for optimizationEvolutionary algorithmLocal search (optimization)businessMetaheuristicMulti-objective optimizationEvolutionary programmingEvolutionary computationMathematics2009 IEEE Congress on Evolutionary Computation
researchProduct

Design of a Permanent Magnet Synchronous Generator using Interactive Multiobjective Optimization

2017

We consider an analytical model of a permanent magnet synchronous generator and formulate a mixed-integer constrained multiobjective optimization problem with six objective functions. We demonstrate the usefulness of solving such a problem by applying an interactive multiobjective optimization method called NIMBUS. In the NIMBUS method, a decision is iteratively involved in the optimization process and directs the solution process in order to find her/his most preferred Pareto optimal solution for the problem. We also employ a commonly used noninteractive evolutionary multiobjective optimization method NSGA-II to generate a set of solutions that approximates the Pareto set and demonstrate t…

Mathematical optimizationPareto optimizationstator windings synchronous generatorsComputer science02 engineering and technologyPermanent magnet synchronous generatorpermanent magnet machines01 natural sciencesMulti-objective optimizationSet (abstract data type)optimointi0103 physical sciences0202 electrical engineering electronic engineering information engineeringElectrical and Electronic Engineeringmagnetic circuitsta113010302 applied physicsta213pareto-tehokkuus020208 electrical & electronic engineeringDesign toolsPareto principleProcess (computing)Control engineeringstator windingsControl and Systems Engineeringsynchronous generatorsdesign toolspermanent magnet (PM) machinesgenerators
researchProduct

A Visualizable Test Problem Generator for Many-Objective Optimization

2022

Visualizing the search behavior of a series of points or populations in their native domain is critical in understanding biases and attractors in an optimization process. Distancebased many-objective optimization test problems have been developed to facilitate visualization of search behavior in a two-dimensional design space with arbitrarily many objective functions. Previous works have proposed a few commonly seen problem characteristics into this problem framework, such as the definition of disconnected Pareto sets and dominance resistant regions of the design space. The authors’ previous work has advanced this research further by providing a problem generator to automatically create use…

Mathematical optimizationProcess (engineering)Computer sciencevisualisointimulti-objective test problemsPareto principleevolutionary optimizationmonitavoiteoptimointiMulti-objective optimizationTheoretical Computer ScienceDomain (software engineering)Visualizationtest suiteRange (mathematics)avoin lähdekoodioptimointiComputational Theory and MathematicsTest suitebenchmarkingongelmanratkaisuvisualizationSoftwareGenerator (mathematics)IEEE Transactions on Evolutionary Computation
researchProduct