The library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. These are artificial intelligence algorithms implemented for the kind of people that like to implement algorithms themselves.
oj! Algorithms
OptaPlanner quick starts for AI optimization: many use cases shown in many different technologies.
The open source AI solver. Timefold is the successor of OptaPlanner, by the OptaPlanner team. Optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling and other planning problems
Solving and GUI demonstration of traditional N-Queens Problem using Hill Climbing, Simulated Annealing, Local Beam Search, and Genetic Algorithm.
chameleonQuant was born as an open-source Java framework to help enthusiast quants to implement system trading strategies and dynamic portfolio trading systems using advanced optimization techniques, machine learning, and deep learning techniques.
Genetic-programming framework for various genetic programming paradigms such as linear genetic programming, tree genetic programming, gene expression programming, etc
Java Constraint Solvers for Vehicle Routing Problem (VRP)
Convex optimization for java and scala, built on Apache Commons Math
A genetic algorithm implementation of the binary Knapsack problem.
Library for numerical optimization of functions written in pure Java.
A mobile app similar to Amazon and other product delivery apps, made a project for getting hands on with payment, designing & tons of errors ^_^
The source code examples for the book "An Introduction to Optimization Algorithms"
Java compilation and optimization benchmark that integrates EO, 𝜑-calculus, JEO, OPEO, and INEO optimizers
Neural Networks in Java 8 with CuDNN and Aparapi
NSGA-II and GA: Implementation of Non-dominated Sorting Genetic Algorithm (NSGA-II) and Binary Genetic Algorithm for Combinatorial Optimization
Solving the NP-hard Multiple Depot Vehicle Routing Problem with a Genetic Algorithm
optimization algorithm that leverages dynamic programming to solve a group interval scheduling maximization problem.
Evaluating Pareto-fronts generated by jMetal Framework
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