To overcome these challenges, we have developed the Molecular multiobjective optimization of Monte Carlo Tree Search (MCTS) and Non-Superiority Ranking Genetic Algorithm II (NSGA-II)-MNopt, which ...

A hybrid intelligent algorithm integrating Q-learning is innovatively designed, using a genetic algorithm as the main framework while embedding a quay crane allocation module and dynamically selecting ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by ...

We present an artificial intelligence-guided approach to design durable and chemically recyclable ring-opening polymerization (ROP) class polymers. This approach employs a genetic algorithm (GA) that ...

The Orienteering Problem (OP) is a well-known route optimization problem with various real-world applications. It aims at finding the most valuable path by visiting a set of nodes within a given path ...

About This project uses Genetic Algorithms to optimize base station placement, minimizing costs and ensuring coverage in three Istanbul neighborhoods. Developed in Python with Selenium and Folium, it ...

The problem involves placing 8 chess queens on an 8x8 chessboard such that no two queens threaten each other. The Genetic Algorithm is an evolutionary algorithm inspired by the process of natural ...

This model frames the problem of correcting source code security concerns as a dual-objective optimization task, balancing code security and functionality. Using a unique contrastive loss function, ...