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The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms
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Outgoing claims: the papers this work cites, builds on, or argues with.
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How to Use the Two Sample t‐Test
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PRICAI 2006: trends in artificial intelligence : 9th Pacific Rim international conference on artificial intelligence, Guilin, China, August 7-11, 2006, Proceedings
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Differential Evolution: A Practical Approach to Global Optimization
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The CMA Evolution Strategy: A Comparing Review
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A Classification of Hyper-heuristic Approaches
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Applications of Evolutionary Computation
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Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing
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Population Size in Differential Evolution
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Applications of Evolutionary Computation
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Rotation Invariance and Rotated Problems: An Experimental Study on Differential Evolution
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Wilcoxon-Signed-Rank Test
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Computer Aided Systems Theory – EUROCAST 2011
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Parameter Meta-optimization of Metaheuristic Optimization Algorithms
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Introduction to Evolutionary Computing
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Computer Aided Systems Theory - EUROCAST 2003
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A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability
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Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
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Self-adaptive differential evolution algorithm using population size reduction and three strategies
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Self-adaptive fruit fly optimizer for global optimization
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Compact Differential Evolution Light: High Performance Despite Limited Memory Requirement and Modest Computational Overhead
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jMetal: A Java framework for multi-objective optimization
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Simulated annealing algorithm with adaptive neighborhood
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A meta optimisation analysis of particle swarm optimisation velocity update equations for watershed management learning
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Benchmarking discrete optimization heuristics with IOHprofiler
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Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems
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Barnacles Mating Optimizer: A new bio-inspired algorithm for solving engineering optimization problems
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Ockham’s Razor in memetic computing: Three stage optimal memetic exploration
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Black hole: A new heuristic optimization approach for data clustering
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Parallel memetic structures
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Compact Particle Swarm Optimization
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An analysis on separability for Memetic Computing automatic design
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Structural bias in population-based algorithms
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HyperSPAM: A study on hyper-heuristic coordination strategies in the continuous domain
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Infeasibility and structural bias in differential evolution
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An evolutionary gravitational search-based feature selection
inferredcites →https://doi.org/10.1016/j.ins.2021.09.058openalex-snapshot
Differential evolution outside the box
inferredcites →https://doi.org/10.1016/j.knosys.2015.07.006openalex-snapshot
Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm
inferredcites →https://doi.org/10.1016/j.swevo.2018.08.013openalex-snapshot
A study on rotation invariance in differential evolution
inferredcites →https://doi.org/10.1016/j.swevo.2019.04.008openalex-snapshot
Bio-inspired computation: Where we stand and what's next
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Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art
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The F-test of homoscedasticity for correlated normal variables
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An improvement of the standard genetic algorithm fighting premature convergence in continuous optimization
inferredcites →https://doi.org/10.1023/a:1016355715164openalex-snapshot
Simple Explanation of the No Free Lunch Theorem of Optimization
inferredcites →https://doi.org/10.1023/a:1021251113462openalex-snapshot
Simple Explanation of the No-Free-Lunch Theorem and Its Implications
inferredcites →https://doi.org/10.1037/h0078850openalex-snapshot
Rank transformations and the power of the Student t test and Welch t' test for non-normal populations with unequal variances.
inferredcites →https://doi.org/10.1046/j.1523-1739.2003.01236.xopenalex-snapshot
Correlation between Fitness and Genetic Diversity
inferredcites →https://doi.org/10.1057/jors.2013.71openalex-snapshot
Hyper-heuristics: a survey of the state of the art
inferredcites →https://doi.org/10.1063/1.5089969openalex-snapshot
A comparison of three differential evolution strategies in terms of early convergence with different population sizes
inferredcites →https://doi.org/10.1063/1.5089971openalex-snapshot
Improving (1+1) covariance matrix adaptation evolution strategy: A simple yet efficient approach
inferredcites →https://doi.org/10.1063/1.5089972openalex-snapshot
Structural bias in differential evolution: A preliminary study
inferredcites →https://doi.org/10.1080/03052150500384759openalex-snapshot
Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization
inferredcites →https://doi.org/10.1080/03610929508831533openalex-snapshot
Some p-variate adaptations of the shapiro-wilk test of normality
inferredcites →https://doi.org/10.1080/0952813x.2015.1042530openalex-snapshot
A new bio-inspired optimisation algorithm: Bird Swarm Algorithm
inferredcites →https://doi.org/10.1093/jee/39.2.269openalex-snapshot
Individual Comparisons of Grouped Data by Ranking Methods
inferredcites →https://doi.org/10.1109/4235.585893openalex-snapshot
No free lunch theorems for optimization
inferredcites →https://doi.org/10.1109/4235.771163openalex-snapshot
Evolutionary programming made faster
inferredcites →https://doi.org/10.1109/cec.2007.4425083openalex-snapshot
Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition
inferredcites →https://doi.org/10.1109/cec.2010.5586034openalex-snapshot
MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimization
inferredcites →https://doi.org/10.1109/cec.2013.6557754openalex-snapshot
Single particle algorithms for continuous optimization
inferredcites →https://doi.org/10.1109/cec.2018.8477837openalex-snapshot
Mushroom Reproduction Optimization (MRO): A Novel Nature-Inspired Evolutionary Algorithm
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Can Single Solution Optimisation Methods Be Structurally Biased?
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A Separability Prototype for Automatic Memes with Adaptive Operator Selection
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PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
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Solving nonlinear optimization problems by Differential Evolution with a rotation-invariant crossover operation using Gram-Schmidt process
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Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
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Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems
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JADE: Adaptive Differential Evolution With Optional External Archive
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Cooperatively Coevolving Particle Swarms for Large Scale Optimization
inferredcites →https://doi.org/10.1109/tevc.2013.2297160openalex-snapshot
Enhancing Differential Evolution Utilizing Eigenvector-Based Crossover Operator
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An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization
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MULTI-STRATEGY COEVOLVING AGING PARTICLE OPTIMIZATION
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A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies
inferredcites →https://doi.org/10.1145/1570256.1570342openalex-snapshot
Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed
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Completely Derandomized Self-Adaptation in Evolution Strategies
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A New Heuristic Optimization Algorithm: Harmony Search
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On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
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A note on preliminary tests of equality of variances
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Novel Memetic Structures (raw data & extended results)
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Differential evolution outside the box - extended results
inferredcites →https://doi.org/10.17632/psp65d2nbcopenalex-snapshot
Raw data & extended results for: a study on rotation invariance in differential evolution
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Infeasibility and structural bias in Differential Evolution - Extended Results
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Mathematical statistics and data analysis, by John A. Rice. Pp 595.1988. ISBN 0-534-08247-5 (Wadsworth & Brooks/Cole)
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A Simple Sequentially Rejective Multiple Test Procedure
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An Improved Squirrel Search Algorithm for Global Function Optimization
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The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms
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T test as a parametric statistic
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The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation
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Holm’s Sequential Bonferroni Procedure
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The Stochastic Optimisation Software (SOS) platform
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Simplified bacterial foraging optimization with quorum sensing for global optimization
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Can Compact Optimisation Algorithms Be Structurally Biased?
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Analysis of Structural Bias in Differential Evolution Configurations
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Towards a software tool for general meal optimisation
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Nonlinear crossing strategy-based particle swarm optimizations with time-varying acceleration coefficients
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An adaptive gravitational search algorithm for optimizing mechanical engineering design and machining problems
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An improved Jaya optimization algorithm with Lévy flight
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Differential evolution outside the box
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Switching from exploration to exploitation in gravitational search algorithm based on diversity with Chaos
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Re-sampled inheritance compact optimization
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PSO based data clustering with a different perception
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Can Single Solution Optimisation Methods Be Structurally Biased?
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BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
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OPTION: OPTImization Algorithm Benchmarking ONtology
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Is there anisotropy in structural bias?
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Emergence of structural bias in differential evolution
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IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
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The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond
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Gradual spatial constraint feature selection for robust biomarker discovery in high-dimensional gene expression data
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Multiple Instance Learning with Differential Evolutionary Pooling
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Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration
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EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
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