Papers Evolutionary Algorithms
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Scaling Multi-Objective Security Games Provably via Space Discretization Based Evolutionary Search
In the field of security, multi-objective security games (MOSGs) allow defenders to simultaneously protect targets from multiple heterogeneous attackers. MOSGs aim to simultaneously maximize all the heterogeneous payoffs…
Evolutionary AlgorithmsThe Impact of Asynchrony on Parallel Model-Based EAs
In a parallel EA one can strictly adhere to the generational clock, and wait for all evaluations in a generation to be done. However, this idle time limits the throughput of the algorithm and wastes computational resourc…
Evolutionary AlgorithmsGBO:AMulti-Granularity Optimization Algorithm via Granular-ball for Continuous Problems
Optimization problems aim to find the optimal solution, which is becoming increasingly complex and difficult to solve. Traditional evolutionary optimization methods always overlook the granular characteristics of solutio…
Evolutionary AlgorithmsTowards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms
Parameter control has succeeded in accelerating the convergence process of evolutionary algorithms. While empirical and theoretical studies have shed light on the behavior of algorithms for single-objective optimization,…
BenchmarkingEvolutionary AlgorithmsEvolutionary Design of the Memory Subsystem
The memory hierarchy has a high impact on the performance and power consumption in the system. Moreover, current embedded systems, included in mobile devices, are specifically designed to run multimedia applications, whi…
Evolutionary AlgorithmsEvolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits
Evolutionary multi-objective algorithms have been widely shown to be successful when utilized for a variety of stochastic combinatorial optimization problems. Chance constrained optimization plays an important role in co…
Combinatorial OptimizationEvolutionary AlgorithmsEvolutionary Computation in Action: Feature Selection for Deep Embedding Spaces of Gigapixel Pathology Images
One of the main obstacles of adopting digital pathology is the challenge of efficient processing of hyperdimensional digitized biopsy samples, called whole slide images (WSIs). Exploiting deep learning and introducing co…
Decision MakingEvolutionary Algorithmsfeature selectionwhole slide imagesImproving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration
Quality-Diversity (QD) algorithms have recently gained traction as optimisation methods due to their effectiveness at escaping local optima and capability of generating wide-ranging and high-performing solutions. Recentl…
DiversityEvolutionary AlgorithmsLasting Diversity and Superior Runtime Guarantees for the $(μ+1)$ Genetic Algorithm
Most evolutionary algorithms (EAs) used in practice employ crossover. In contrast, only for few and mostly artificial examples a runtime advantage from crossover could be proven with mathematical means. The most convinci…
DiversityEvolutionary AlgorithmsTight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions
In a seminal paper in 2013, Witt showed that the (1+1) Evolutionary Algorithm with standard bit mutation needs time $(1+o(1))n \ln n/p_1$ to find the optimum of any linear function, as long as the probability $p_1$ to fl…
Evolutionary AlgorithmsMulti-objective optimization of energy consumption and execution time in a single level cache memory for embedded systems
Current embedded systems are specifically designed to run multimedia applications. These applications have a big impact on both performance and energy consumption. Both metrics can be optimized selecting the best cache c…
Evolutionary AlgorithmsPareto Dominance Archive and Coordinated Selection Strategy-Based Many-Objective Optimizer for Protein Structure Prediction
Protein structure prediction (PSP) is predicting the three-dimensional of protein from its amino acid sequence only based on the information hidden in the protein sequence. One of the efficient tools to describe this inf…
Evolutionary AlgorithmsProtein FoldingProtein Structure PredictionEfficient Generator of Mathematical Expressions for Symbolic Regression
We propose an approach to symbolic regression based on a novel variational autoencoder for generating hierarchical structures, HVAE. It combines simple atomic units with shared weights to recursively encode and decode th…
Evolutionary AlgorithmsregressionSymbolic RegressionForecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods
One of the key tasks in the economy is forecasting the economic agents' expectations of the future values of economic variables using mathematical models. The behavior of mathematical models can be irregular, including c…
Decision MakingEvolutionary AlgorithmsQ-LearningA Three-Phase Artificial Orcas Algorithm for Continuous and Discrete Problems
In this paper, a new swarm intelligence algorithm based on orca behaviors is proposed for problem solving. The algorithm called artificial orca algorithm (AOA) consists of simulating the orca lifestyle and in particular …
Evolutionary AlgorithmsTools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games
The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in game-oriented research and industry. A spe…
Evolutionary AlgorithmsFourier Analysis Meets Runtime Analysis: Precise Runtimes on Plateaus
We propose a new method based on discrete Fourier analysis to analyze the time evolutionary algorithms spend on plateaus. This immediately gives a concise proof of the classic estimate of the expected runtime of the $(1+…
Evolutionary AlgorithmsELEA -- Build your own Evolutionary Algorithm in your Browser
We provide an open source framework to experiment with evolutionary algorithms which we call "Experimenting and Learning toolkit for Evolutionary Algorithms (ELEA)". ELEA is browser-based and allows to assemble evolution…
Evolutionary AlgorithmsSparse Mutation Decompositions: Fine Tuning Deep Neural Networks with Subspace Evolution
Neuroevolution is a promising area of research that combines evolutionary algorithms with neural networks. A popular subclass of neuroevolutionary methods, called evolution strategies, relies on dense noise perturbations…
DiversityEnsemble LearningEvolutionary AlgorithmsBenchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
Submodular functions play a key role in the area of optimization as they allow to model many real-world problems that face diminishing returns. Evolutionary algorithms have been shown to obtain strong theoretical perform…
BenchmarkingEvolutionary Algorithms