نتایج جستجو برای: dominate sorting genetic algorithm ii

تعداد نتایج: 1873964  

Journal: :Energies 2022

In this work, a novel agent-based day-ahead power management scheme is proposed for multiple-microgrid distribution systems with the intent of reducing operational costs and improving system resilience. The sharing algorithm executes within each microgrid (MG) locally, neighboring MGs cooperate via multi-agent cooperation scheme, established to model communication among agents. agent modeled as...

This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 a...

M. Mohebbi, S. Bakhshinezhad,

In this paper, a procedure has been introduced to the multi-objective optimal design of semi-active tuned mass dampers (SATMDs) with variable stiffness for nonlinear structures considering soil-structure interaction under multiple earthquakes. Three bi-objective optimization problems have been defined by considering the mean of maximum inter-story drift as safety criterion of structural compone...

Journal: :ACM/IMS transactions on data science 2021

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. hybrid algorithm, hybridization Nelder-Mead Simplex and Non-dominated Sorting Genetic Algorithm (NSGA), named (SNSGA), to optimize timetable problem coordinate shared access. algorithm utilizes in terms exploration NSGA sorting local optimum points with consideration pot...

Journal: :IEEE Transactions on Transportation Electrification 2023

Railway electrification has attracted substantial interest in recent years as a key part of the global effort to achieve transport decarbonization. To improve energy efficiency train operations, particular is optimization speed trajectories. However, most studies formulate problem single-objective model and do not take into account mass uncertainty associated with passenger load variations. Thi...

2012
Ashish Saini Amit Saraswat

This paper presents an application of elitist non-dominated sorting genetic algorithm (NSGA-II) for solving a multi-objective reactive power market clearing (MO-RPMC) model. In this MO-RPMC model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and voltage stability enhancement index (VSEI) are optimized simultaneous...

Journal: :Iraqi journal of science 2021

Feature selection, a method of dimensionality reduction, is nothing but collecting range appropriate feature subsets from the total number features. In this paper, point by explanation review about selection in segment preferred affairs and its appraisal techniques are discussed. I will initiate my conversation with straightforward approach so that we consider taking care features issues depend...

2003
Xuan Jiang Deepti Chafekar Khaled Rasheed

In this paper we propose a novel approach for solving constrained multi-objective optimization problems using a steady state GA and reduced models. Our method called Objective Exchange Genetic Algorithm for Design optimization (OEGADO) is intended for solving real-world application problems that have many constraints and very small feasible regions. OEGADO runs several GAs concurrently with eac...

Journal: :IEEE Trans. Evolutionary Computation 2002
Kalyanmoy Deb Samir Agrawal Amrit Pratap T. Meyarivan

Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( ) computational complexity (where is the number of objectives and is the population size); 2) nonelitism approach; and 3) the need for specifying a sharing parameter. In this paper, we suggest a nondominated sorting-based multiobjective EA (MOEA), called nondominate...

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