Hands-On Genetic Algorithms with Python by Eyal Wirsansky is a new book which explores the world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine ...

Lysa Porth, Jeffrey Pai, Milton Boyd, A Portfolio Optimization Approach Using Combinatorics With a Genetic Algorithm for Developing a Reinsurance Model, The Journal of Risk and Insurance, Vol. 82, No.

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 ...

Our inclusion of skewness and kurtosis makes portfolio optimization a nonlinear, nonconvex and multi-objective problem; this has been solved with the use of a genetic algorithm. Empirical results ...

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...

Learn how to implement Adam optimization from the ground up in Python! This step-by-step guide will walk you through the algorithm's mechanics and how to use it in machine learning projects. 🚀 ...