Author Archives: Community

Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression

When learning from high-dimensional data for symbolic regression (SR), genetic programming (GP) typically could not generalize well. Feature selection, as a data preprocessing method, can potentially contribute not only to improving the efficiency of l… Continue reading

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DMOEA- $varepsilon text{C}$ : Decomposition-Based Multiobjective Evolutionary Algorithm With the $varepsilon $ -Constraint Framework

Decomposition is an efficient and prevailing strategy for solving multiobjective optimization problems (MOPs). Its success has been witnessed by the multiobjective evolutionary algorithm MOEA/D and its variants. In decomposition-based methods, an MOP i… Continue reading

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IEEE Transactions on Evolutionary Computation Society Information

Provides a listing of current committee members and society officers. Continue reading

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A Weighted Biobjective Transformation Technique for Locating Multiple Optimal Solutions of Nonlinear Equation Systems

Due to the fact that a nonlinear equation system (NES) may contain multiple optimal solutions, solving NESs is one of the most important challenges in numerical computation. When applying evolutionary algorithms to solve NESs, two issues should be cons… Continue reading

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IEEE World Congress on Computational Intelligence

Describes the above-named upcoming conference event. May include topics to be covered or calls for papers. Continue reading

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A Surrogate Assisted Approach for Single-Objective Bilevel Optimization

Bilevel optimization refers to a hierarchical problem in which optimization needs to be performed at two nested levels, namely the upper level and the lower level. The aim is to identify the optimum of the upper level problem, subject to optimality of … Continue reading

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Table of contents

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A Two-Phase Differential Evolution for Uniform Designs in Constrained Experimental Domains

In many real-world engineering applications, a uniform design needs to be conducted in a constrained experimental domain that includes linear/nonlinear and inequality/equality constraints. In general, these constraints make the constrained experimental… Continue reading

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Improving Evolutionary Algorithms in a Continuous Domain by Monitoring the Population Midpoint

It is advocated that monitoring the population midpoint allows for improving the efficiency of population-based evolutionary algorithms (EAs) in $mathbb {R}^{ d}$ . The theoretical motivation supporting this hypothesis is provided in this letter, and… Continue reading

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IEEE Transactions on Evolutionary Computation publication information

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. Continue reading

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