Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

Evolutionary algorithms (EAs) represent a class of heuristic optimisation methods inspired by natural selection and Mendelian genetics. They iteratively evolve a population of candidate solutions ...

One of the primary challenges in wind energy development is optimizing the spatial layout of wind turbines within a given site. Poor turbine placement can lead to reduced energy capture due to wake ...

The code that I wrote decouples the blackjack engine from the genetic algorithm, so perhaps I will try this and compare! The reason that your solution would work is that each cell’s strategy ...

Does evolutionary computation ring a bell? In computer science, it’s the family of algorithms for global optimization inspired by biological evolution.

This paper frames hardware-aware neural network pruning as a multi-objective optimization problem and introduces HAMP, a memetic Multi-Objective Evolutionary Algorithm (MOEA) that optimizes both ...

The promise of evolutionary algorithms has been around for several years, offering organizations the elusive prospect of an advanced self-learning approach for artificial intelligence (AI).. A key ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms ...

Evolutionary Optimization Algorithm Step one is to select two good, but not necessarily best, parent individuals from the population. In step two, crossover is used to generate two child individuals, ...

SAN JOSE, Calif., March 18, 2025--TurinTech has launched Artemis, the world’s first Agentic and Evolutionary AI platform to optimize and validate enterprise codebases.