Particle Swarm Optimization (PSO) algorithms are a shape of evolutionary computing that performs by simulating the conduct of a swarm of digital particles that pass among a described seek area with ...

Simple Numerical Optimization Using an Evolutionary Algorithm with C#. Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms ...

Introduction. In recent years, the development of evolutionary computation has attracted extensive attention. Based on the Darwinian theorem of “Survival of the Fittest” (Dawkins, 2006; Ma et al., ...

Abstract: Evolutionary multitask optimization (EMTO) can solve multiple tasks simultaneously by leveraging the relevant information between tasks, but existing EMTO algorithms do not take into account ...

New Evolutionary Computing Developments Optimize Complex Problem Solving Date: May 21, 2009 Source: Facultad de Informática de la Universidad Politécnica de Madrid ...

For example, the classic Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D), and Multiobjective Particle Swarm Optimization ...

To address these limitations, this paper proposes Evolutionary Policy Optimization (EPO), a hybrid algorithm that integrates neuroevolution with policy gradient methods for policy optimization. EPO ...

Tan Liu, Qinyun Yuan, Lina Wang, Yonggang Wang, Nannan Zhang, Multi-objective optimization for oil-gas production process based on compensation model of comprehensive energy consumption using improved ...