Search results for "Multi-Objective Optimization"

showing 10 items of 192 documents

Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II

2022

Detailed parametric analysis and measurements are required to reduce building energy usage while maintaining acceptable thermal conditions. This research suggested a system that combines Building Information Modeling (BIM), machine learning, and the non-dominated sorting genetic algorithm-II (NSGA II) to investigate the impact of building factors on energy usage and find the optimal design. A plugin is developed to receive sensor data and export all necessary information from BIM to MSSQL and Excel. The BIM model was imported to IDA Indoor Climate and Energy (IDA ICE) to execute an energy consumption simulation and then a pairwise test to produce the sample data set. To study the data set a…

Mechanical EngineeringBuilding and ConstructionBuilding energy consumptionThermal comfort/dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_productionMulti-objective optimizationVDP::Teknologi: 500Building information modelling/dk/atira/pure/sustainabledevelopmentgoals/climate_actionSDG 13 - Climate ActionNSGA IIElectrical and Electronic EngineeringLinear regressionSDG 12 - Responsible Consumption and ProductionCivil and Structural Engineering
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Multi-Objective and Multi-Criteria Analysis for Optimal Pump Scheduling in Water Systems

2018

This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.

Multi-objective optimizationMathematical optimizationWater distribution systemsComputer scienceMulti criteriaScheduling (production processes)Optimal pump schedulingMulticriteria analysisEPiC Series in Engineering
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k-out-of-n systems: an exact formula for the stationary availability and multi-objective configuration design based on mathematical programming and T…

2018

[EN] Reliability and availability analyses are recognized as essential for guiding decision makers in the implementation of actions addressed to improve the technical and economical performance of complex systems. For industrial systems with reparable components, the most interesting parameter used to drive maintenance is the stationary availability. In this regard, the present paper proposes an exact formula for computing the system stationary availability of a k-out-of-n system. Such a formula is proved to be in agreement with the fundamental theorem of Markov chains. Then, a multi-objective mathematical model is formulated for choosing the optimal system configuration design. The Pareto …

Multi-objective optimizationStationary availabilityMarkov chainsK-out-of-n systemMarkov chainSettore ING-IND/17 - Impianti Industriali MeccaniciTOPSISMATEMATICA APLICADA
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Genetic Algorithms: A Decision Tool in Industrial Disassembly

2008

In the recycling process of the Waste Electrical and Electronic Equipment (WEEE) the disassembly process has a central role. Disassembly is not the reverse of the assembly process, real difficulties occur in the tasks assignment process of the disassembly operations. Since this is a multi objective optimization problem, we prove that genetic algorithms provide a useful multi-criteria decision tool in the industrial disassembly process.

Multiobjective optimization problemDecision toolWorkstationlawComputer scienceWaste recoveryHardware_REGISTER-TRANSFER-LEVELIMPLEMENTATIONIndustrial engineeringMulti-objective optimizationElectronic equipmentScheduling (computing)law.invention2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing
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On Generalizing Lipschitz Global Methods forMultiobjective Optimization

2015

Lipschitz global methods for single-objective optimization can represent the optimal solutions with desired accuracy. In this paper, we highlight some directions on how the Lipschitz global methods can be extended as faithfully as possible to multiobjective optimization problems. In particular, we present a multiobjective version of the Pijavskiǐ-Schubert algorithm.

Multiobjective optimization problemMathematical optimizationComputer scienceLipschitz continuityMulti-objective optimizationComputer Science::Databases
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NIMBUS — Interactive Method for Nondifferentiable Multiobjective Optimization Problems

1996

An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. We assume that every objective function is to be minimized 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.

Multiobjective optimization problemMathematical optimizationPoint (geometry)Decision makerBundle methodsMulti-objective optimizationMathematics
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Interactive Nonlinear Multiobjective Procedures

2006

An overview of the interactive methods for solving nonlinear multiple criteria decision making problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory compromise can be found. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated.

Nonlinear systemMathematical optimizationComputer scienceCompromisemedia_common.quotation_subjectMultiple criteriaDecision makerMulti-objective optimizationPreferenceNonlinear programmingmedia_common
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Some Methods for Nonlinear Multi-objective Optimization

2001

A general overview of nonlinear multiobjective optimization methods is given. The basic features of several methods are introduced so that an appropriate method could be found for different purposes. The methods are classified according to the role of a decision maker in the solution process. The main emphasis is devoted to interactive methods where the decision maker progressively provides preference information so that the most satisfactory solution can be found.

Nonlinear systemMathematical optimizationComputer scienceMulti-objective optimizationPreferenceNonlinear programming
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A fuzzy programming method for optimization of autonomous logistics objects

2013

Recently several studies have explored the realization of autonomous control in production and logistic operations. In doing so, it has been tried to transmit the merit of decision-making from central controllers with offline decisions to decentralized controllers with local and real-time decision makings. However, this mission has still some drawbacks in practice. Lack of global optimization is one of them, i.e., the lost chain between the autonomous decentralized decisions at operational level and the centralized mathematical optimization with offline manner at tactical and strategic levels. This distinction can be reasonably solved by considering fuzzy parameters in mathematical programm…

Operations researchComputer scienceFuzzy setFuzzy set operationsRobust optimizationControl engineeringMulti-objective optimizationGlobal optimizationRealization (systems)Fuzzy logicAutonomous logistics2013 IEEE International Conference on Mechatronics (ICM)
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A Generalized Framework for Optimal Sizing of Distributed Energy Resources in Micro-Grids Using an Indicator-Based Swarm Approach

2014

In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated usin…

Optimal designMathematical optimizationEngineeringNSGA-IIbusiness.industrymicrogridsPareto principleGlow-worm optimizationindicator based evolutionary algorithmMulti-objective optimizationComputer Science ApplicationsSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicamicrogridPower system simulationControl and Systems EngineeringDistributed generationmicrogrids;indicator based evolutionary algorithm;Glow-worm optimization;planning;NSGA-IICapital costMicrogridplanningElectrical and Electronic EngineeringbusinessActivity-based costingInformation SystemsIEEE Transactions on Industrial Informatics
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