Search results for "objective"

showing 10 items of 505 documents

2021

One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the non-dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the streng…

Mathematical optimizationGeneral Computer ScienceComputer scienceSortingEvolutionary algorithmPareto principleParticle swarm optimizationComputingMilieux_LEGALASPECTSOFCOMPUTINGContext (language use)Multi-objective optimizationSoftware deployment11. SustainabilityElectrical and Electronic EngineeringIntelligent transportation systemInternational Journal of Electrical and Computer Engineering (IJECE)
researchProduct

Best compromise solution for a new multiobjective scheduling problem

2006

In future wireless networks, a mobile terminal will be able to communicate with a service provider using several network connections. These connections to networks will have different properties and they will be priced separately. In order to minimize the total communication time and the total transmission costs, an automatic method for selecting the network connections is needed. Here, we describe the network connection selection problem and formulate it mathematically. We discuss solving the problem and analyse different multiobjective optimization approaches for it.

Mathematical optimizationGeneral Computer ScienceJob shop schedulingWireless networkComputer scienceModeling and SimulationManagement Science and Operations ResearchService providerTransmission timeMulti-objective optimizationTelecommunications networkAssignment problemScheduling (computing)Computers & Operations Research
researchProduct

Optimal Sizing and Siting of Distributed Energy Resources Considering Public and Private Incentive Policies

2008

The present work presents the formulation and solution approach for the problem of optimal sizing and siting of distributed energy resources based on Photovoltaic, PV, technology. The considered system is an isolated grid (small island) and the parts involved are the utility and the customers. As it happens in islands, the same utility generates and delivers energy to customers, for this reason, the installation of dispersed generation units is beneficial for reducing power losses, regularizing the voltage profile, but also for increasing the profit. The problem is solved by means of the Non dominated sorting Genetic Algorithm II, NSGA-II, identifying the optimal size and location of PV sys…

Mathematical optimizationIncentiveOperations researchbusiness.industryComputer scienceDistributed generationPhotovoltaic systembusinessGridMulti-objective optimizationSizingExternalityProfit (economics)
researchProduct

Synchronous approach in interactive multiobjective optimization

2006

We introduce a new approach in the methodology development for interactive multiobjective optimization. The presentation is given in the context of the interactive NIMBUS method, where the solution process is based on the classification of objective functions. The idea is to formulate several scalarizing functions, all using the same preference information of the decision maker. Thus, opposed to fixing one scalarizing function (as is done in most methods), we utilize several scalarizing functions in a synchronous way. This means that we as method developers do not make the choice between different scalarizing functions but calculate the results of different scalarizing functions and leave t…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputer sciencebusiness.industrymedia_common.quotation_subjectContext (language use)Management Science and Operations ResearchMultiple-criteria decision analysisMulti-objective optimizationIndustrial and Manufacturing EngineeringNonlinear programmingNonlinear systemModeling and SimulationSoftware systemArtificial intelligenceFunction (engineering)businessmedia_commonEuropean Journal of Operational Research
researchProduct

The price of multiobjective robustness : Analyzing solution sets to uncertain multiobjective problems

2021

Defining and finding robust efficient solutions to uncertain multiobjective optimization problems has been an issue of growing interest recently. Different concepts have been published defining what a “robust efficient” solution is. Each of these concepts leads to a different set of solutions, but it is difficult to visualize and understand the differences between these sets. In this paper we develop an approach for comparing such sets of robust efficient solutions, namely we analyze their outcomes under the nominal scenario and in the worst case using the upper set-less order from set-valued optimization. Analyzing the set of nominal efficient solutions, the set of minmax robust efficient …

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputer sciencemultiobjective robust optimizationSolution setpäätöksentukijärjestelmätManagement Science and Operations ResearchMinimaxmonitavoiteoptimointiepävarmuusIndustrial and Manufacturing Engineeringdecision makingRobustness (computer science)Modeling and Simulationuncertaintyprice of robustness
researchProduct

Experiments with classification-based scalarizing functions in interactive multiobjective optimization

2006

In multiobjective optimization methods, the multiple conflicting objectives are typically converted into a single objective optimization problem with the help of scalarizing functions and such functions may be constructed in many ways. We compare both theoretically and numerically the performance of three classification-based scalarizing functions and pay attention to how well they obey the classification information. In particular, we devote special interest to the differences the scalarizing functions have in the computational cost of guaranteeing Pareto optimality. It turns out that scalarizing functions with or without so-called augmentation terms have significant differences in this re…

Mathematical optimizationInformation Systems and ManagementGeneral Computer SciencePareto principleManagement Science and Operations ResearchMulti-objective optimizationMultiple objective programmingIndustrial and Manufacturing EngineeringSet (abstract data type)Nonlinear systemSingle objective optimization problemConflicting objectivesModeling and SimulationBenchmark (computing)MathematicsEuropean Journal of Operational Research
researchProduct

Using box indices in supporting comparison in multiobjective optimization

2009

Because of the conflicting nature of criteria or objectives, solving a multiobjective optimization problem typically requires interaction with a decision maker who can specify preference information related to the objectives in the problem in question. Due to the difficulties of dealing with multiple objectives, the way information is presented plays a very important role. Questions posed to the decision maker must be simple enough and information shown must be easy to understand. For this purpose, visualization and graphical representations can be useful and constitute one of the main tools used in the literature. In this paper, we propose to use box indices to represent information relate…

Mathematical optimizationInformation Systems and ManagementGeneral Computer Sciencebusiness.industryScale (chemistry)Information and Computer ScienceManagement Science and Operations ResearchMachine learningcomputer.software_genreMultiple-criteria decision analysisMulti-objective optimizationIndustrial and Manufacturing EngineeringPreferenceVisualizationSimple (abstract algebra)Modeling and SimulationArtificial intelligenceGraphicsbusinesscomputerMathematicsEuropean Journal of Operational Research
researchProduct

NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point

2010

Most interactive methods developed for solving multiobjective optimization problems sequentially generate Pareto optimal or nondominated vectors and the decision maker must always allow impairment in at least one objective function to get a new solution. The NAUTILUS method proposed is based on the assumptions that past experiences affect decision makers’ hopes and that people do not react symmetrically to gains and losses. Therefore, some decision makers may prefer to start from the worst possible objective values and to improve every objective step by step according to their preferences. In NAUTILUS, starting from the nadir point, a solution is obtained at each iteration which dominates t…

Mathematical optimizationInformation Systems and ManagementInteractive programmingGeneral Computer Sciencebiologymedia_common.quotation_subjectManagement Science and Operations Researchbiology.organism_classificationMulti-objective optimizationIndustrial and Manufacturing EngineeringSightNegotiationIterated functionModeling and SimulationMinificationNautilusOptimal decisionMathematicsmedia_commonEuropean Journal of Operational Research
researchProduct

Interactive Nonconvex Pareto Navigator for Multiobjective Optimization

2019

Abstract We introduce a new interactive multiobjective optimization method operating in the objective space called Nonconvex Pareto Navigator . It extends the Pareto Navigator method for nonconvex problems. An approximation of the Pareto optimal front in the objective space is first generated with the PAINT method using a relatively small set of Pareto optimal outcomes that is assumed to be given or computed prior to the interaction with the decision maker. The decision maker can then navigate on the approximation and direct the search for interesting regions in the objective space. In this way, the decision maker can conveniently learn about the interdependencies between the conflicting ob…

Mathematical optimizationInformation Systems and Managementinteractive multiobjective optimizationGeneral Computer ScienceComputer science0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchSpace (commercial competition)Multi-objective optimizationIndustrial and Manufacturing Engineering0502 economics and businessnonconvex problemsnavigationta113050210 logistics & transportation021103 operations researchpareto-tehokkuuspareto optimality05 social sciencesPareto principlemonitavoiteoptimointinavigointiModeling and Simulationmultiple objective programmingEuropean Journal of Operational Research
researchProduct

Modelling energy storage systems using Fourier analysis: An application for smart grids optimal management

2014

In this paper, a new and efficient model for variables representation, named F-coding, in optimal power dispatch problems for smart electrical distribution grids is proposed. In particular, an application devoted to optimal energy dispatch of Distributed Energy Resources including ideal storage devices is here considered. Electrical energy storage systems, such as any other component that must meet an integral capacity constraint in optimal dispatch problems, have to show the same energy level at the beginning and at the end of the considered timeframe for operation. The use of zero-integral functions, such as sinusoidal functions, for the synthesis of the charge and discharge course of bat…

Mathematical optimizationIntegral constraintMulti-objective evolutionary algorithmbusiness.industryComputer scienceFourier analysiEconomic dispatchSmart gridsMulti-objective optimizationEnergy storageElectrical energy storage systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicaSmart gridDistributed generationComponent (UML)Optimal dispatch of resourcebusinessRepresentation (mathematics)SoftwareEnergy (signal processing)Applied Soft Computing
researchProduct