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[PDF] Top 20 A novel multiobjective evolutionary algorithm based on regression analysis

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A novel multiobjective evolutionary algorithm based on regression analysis

A novel multiobjective evolutionary algorithm based on regression analysis

... continuous multiobjective optimization problem with 𝑚 objective functions is a piecewise continuous (𝑚 − 1)-dimensional manifold in the decision space under some mild ...design multiobjective optimization ... See full document

11

Design and tuning of an evolutionary multiobjective optimisation algorithm

Design and tuning of an evolutionary multiobjective optimisation algorithm

... EMOA based on quadratic programming methods [KSD07] ...criterion based on the convergence of the maximum crowding distance, but it is restricted to elitist EMOA and only tested for ...the algorithm ... See full document

168

The Constrained Mean Semivariance Portfolio Optimization Problem with the Support of a Novel Multiobjective Evolutionary Algorithm

The Constrained Mean Semivariance Portfolio Optimization Problem with the Support of a Novel Multiobjective Evolutionary Algorithm

... Next, we present the process of efficient frontier formu- lation by quoting experimental results based on historical data of FTSE-100. For the first experiment, as a training set we use 63 daily historical ... See full document

8

Hyperspectral classification optimization using multiobjective evolutionary algorithm

Hyperspectral classification optimization using multiobjective evolutionary algorithm

... The novel aspect of this research is about the formulation and the application of the Multiobjective Evolutionary Algorithm (MOEA), which is based on the genetic algorithm, to ... See full document

83

A strength pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization

A strength pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization

... The basic framework of the proposed SPEA/R algorithm is presented in Algorithm 1. SPEA/R starts with an initial pop- ulation and the construction of a predefined set of reference directions, which splits ... See full document

18

Economic Operation of Self Sustained Microgrid Optimal Operation by Multiobjective Evolutionary Algorithm Based on Decomposition

Economic Operation of Self Sustained Microgrid Optimal Operation by Multiobjective Evolutionary Algorithm Based on Decomposition

... Imagery Analysis to Investigate Morphodynamic Changes in Mond Coastal Area, the Persian Gulf, 17th Physics of Estuaries and Coastal Seas (PECS) Conference, Porto de Galinhas, Pernambuco, Brazil, 19-24 October ... See full document

11

Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm

Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm

... the evolutionary multi-objective optimization (EMO) methodol- ogy has been illustrated as a promising tool to analyze the relationships between objectives and calculate the pareto-front ...techniques based ... See full document

14

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

... This paper proposes a novel MCMOEA, for overlapping community detection. In MCMOEA, we introduce the maximal-clique graph by using a set of maximal cliques as nodes and the links among maximal cliques as edges. ... See full document

15

Evolutionary Multiobjective Optimization for Adaptive Dataflow-based Digital Predistortion Architectures

Evolutionary Multiobjective Optimization for Adaptive Dataflow-based Digital Predistortion Architectures

... performed based on multidimensional operational ...a novel evolutionary algorithm framework for multiobjective optimization of DPD ...proposed multiobjective optimization ... See full document

9

Applying Linear Regression and Neural Network Meta-Models for Evolutionary Algorithm Based Simulation Optimization

Applying Linear Regression and Neural Network Meta-Models for Evolutionary Algorithm Based Simulation Optimization

... polynomial analysis. A canonical analysis is then conducted to determine if further exploration needs to be ...ridge analysis may be performed to collect observations along the ridge ...the ... See full document

103

A tutorial on multiobjective optimization: fundamentals and evolutionary methods

A tutorial on multiobjective optimization: fundamentals and evolutionary methods

... a novel mutation scheme, which was the focus of the paper (Huband et ...an algorithm design, in which the choice of indicators is ...Estimation Algorithm (HypE) (Bader and Zitzler 2011) uses a Monte ... See full document

25

Evolutionary multiobjective optimization : review, algorithms, and applications

Evolutionary multiobjective optimization : review, algorithms, and applications

... model-based multiobjective estimation of dis- tribution algorithm ...the algorithm performs the following steps: (i) a probability model of the distribution of the solutions in the popu- ... See full document

320

A novel two-archive strategy for evolutionary many-objective optimization algorithm based on reference points

A novel two-archive strategy for evolutionary many-objective optimization algorithm based on reference points

... Methods based on objectives decomposition. Aggregation-based optimization algorithms use an aggregate function to decompose many ...objectives. Multiobjective Evolutionary Algorithm ... See full document

28

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

... This paper proposes a novel MCMOEA, for overlapping community detection. In MCMOEA, we introduce the maximal-clique graph by using a set of maximal cliques as nodes and the links among maximal cliques as edges. ... See full document

16

Test Case Generation from Activity Diagram Using Multiobjective Evolutionary Algorithm

Test Case Generation from Activity Diagram Using Multiobjective Evolutionary Algorithm

... describe analysis and design ...different evolutionary algorithms and UML based testing has further shown that test cases can be successfully generated covering single or multiple objectives like ... See full document

10

Tchebycheff Method-based Evolutionary Algorithm for Multiobjective Optimization

Tchebycheff Method-based Evolutionary Algorithm for Multiobjective Optimization

... EA-based multiobjective optimization procedure that builds upon the Tchebycheff ...for multiobjective optimization ...the algorithm, a notion borrowed from mathematical ... See full document

39

An adaptation reference-point-based multiobjective evolutionary algorithm

An adaptation reference-point-based multiobjective evolutionary algorithm

... Figure 1: Pareto-optimal solutions (red solid dots) specified by different reference points (grey solid dots). (a) Pareto-optimal solutions specified by nine uniformly distributed reference points on a PF with the same ... See full document

28

An Evolutionary Approach to Active Robust Multiobjective Optimisation

An Evolutionary Approach to Active Robust Multiobjective Optimisation

... existing evolutionary algorithms for multi-objective RO consider Type C uncertainties, represented by added noise to the nominal function val- ...first evolutionary algorithm for robust MOPs were ... See full document

16

A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model

A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model

... the algorithm to the new optimal ...co-evolutionary algorithm; it generates new individuals by selecting representatives of different sub-populations and themselves to recombine and ... See full document

38

Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization

Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization

... Genetic Algorithm, NSGA-II, is undoubtedly the most well-known and referenced algorithm in the multi-objective ...is based on obtaining a new population from the original one by applying the typical ... See full document

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