Search results for " multi-objective optimization"

showing 6 items of 16 documents

Supporting the Sustainable Energy Transition in the Canary Islands: Simulation and Optimization of Multiple Energy System Layouts and Economic Scenar…

2021

The Canary Islands have great potential for the implementation of sustainable energy systems due to its availability of natural resources. The archipelago is not connected to the mainland electricity grid and the current generation system is mainly based on traditional fossil fuel. Therefore, the islands strongly dependent on fuel importations, with high costs due to logistics. Furthermore, due to the inadequate coverage of residential heating and cooling needs, the per capita energy consumption is far below the Spanish national average. This occurrence has inspired an intense debate on the current development model of the Canary Archipelago, which has led to the implementation of actions a…

Science (General)renewable technologies020209 energyPopulationTime horizon02 engineering and technologyTRNSYSsustainable energy transitionQ1-390020401 chemical engineeringsustainable energy transition renewable technologies sustainability in Canary Islands modeling and simulation multiple scenarios multi-objective optimizationmodeling and simulation0202 electrical engineering electronic engineering information engineeringEnergy supply0204 chemical engineeringeducationH1-99education.field_of_studyWind powermultiple scenariosbusiness.industryEnvironmental impact of the energy industryEnergy consumptionEnvironmental economicssustainability in Canary IslandsRenewable energySocial sciences (General)multi-objective optimizationEnvironmental sciencebusinessFrontiers in Sustainable Cities
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A New Meta-Heuristic Multi-Objective Approach For Optimal Dispatch of Dispersed and Renewable Generating Units in Power Distribution Systems

2011

The application of stochastic methods in engineering research and optimization has been increasing over the past few decades. Ant Colony Optimization, in particular, has been attracting growing attention as a promising approach both in discrete and continuous domains. The present work proposes a multi-objective Ant Colony Optimization for continuous domains showing good convergence properties and uniform coverage of the non-dominated front. These properties have been proved both with mathematical test functions and with a complex real world problem. Besides the second part of the chapter presents the application of the new algorithm to the problem of optimal dispatch of dispersed power gene…

Settore ING-IND/33 - Sistemi Elettrici Per L'EnergiaDistribution systemMathematical optimizationstochastic multi-objective optimization multi-objective ant colony optimization optimal power dispatch microgridsbusiness.industryComputer scienceObjective approachOptimal dispatchMeta heuristicbusinessRenewable energyPower (physics)
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Hybrid evolutionary multi-objective optimization with enhanced convergence and diversity

2011

interactive evolutionary multi-objective optimizationNSGA-IIdifferential evolutionevoluutioalgoritmitPIEmultiple criteria decision makingmuuttujathybridialgoritmitmonitavoiteoptimointiEMO-algoritmitPareto-optimitNAUTILUS methodmutationhybrid frameworkachievement scalarizing function
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Optimal design of k-out-of-n systems

2016

The present paper is aimed at finding the best compromise to design a system k-out-of-n reliability configuration by means of the formulation of a multi-objective mathematical model. The Pareto front, which is the set of non-dominated solutions, is determined by considering the stationary availability and the achievable profit as objectives to be simultaneously optimized. The Pareto front represents a useful tool for the analyst to make the choice related to the analyzed design problem. In addition, the knowledge of the Pareto front permits to consider different design scenarios.

k-out-of-n system stationary availability multi-objective optimization Pareto front
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Multi-objective parameter identification via ACOR algorithm

2009

The spreading of advanced constituive models, needed to model complex phenomena, makes necessary to solve difficult parameter identification problems. The need of multiple tests to fully characterize the experimental behaviour makes the parameter identification problem a multi objective one. Unlike conventional techniques, based on the formulation of an aggregate scalar ob- jective function, in the present work the problem is addressed using a new multi objective algorithm obtained extending the continuous Ant Colony Optimization algorithm. Mathematical tests and ap- plication to a real world problem are performed and different performance measures are used to asses the performance of the a…

parameters identification ACOR multi-objective optimization.Settore ICAR/08 - Scienza Delle Costruzioni
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Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

2015

Classical evolutionary multi-objective optimization algorithms aim at finding an approx- imation of the entire set of Pareto optimal solutions. By considering the preferences of a decision maker within evolutionary multi-objective optimization algorithms, it is possible to focus the search only on those parts of the Pareto front that satisfy his/her preferences. In this paper, an extended preference-based evolutionary algorithm has been proposed for solving multi-objective optimiza- tion problems. Here, concepts from an interactive synchronous NIMBUS method are borrowed and combined with the R-NSGA-II algorithm. The proposed synchronous R-NSGA-II algorithm uses preference information provid…

ta113Mathematical optimizationinteractive multi-objective optimizationApplied MathematicsEvolutionary algorithmApproxDecision makerMulti-objective optimizationscalarizing functionSet (abstract data type)Pareto optimalevolutionary multi-objective optimizationpreference-based evolutionary algorithmsFocus (optics)Preference (economics)Information SystemsMathematicsInformatica
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