A high-performance, modular Go library for exploring hybrid genetic algorithms (SGA, NSGA-II, SPEA2, FR-NSGA2) applied to multi-objective graph layout and other optimization problems.

Contains coursework amendments related to `Genetic Algorithms & Optimization`

C code for Strength Pareto Evolutionary Algorithm from authors Eckart Zitzler, Marco Laumanns, and Lothar Thiele

Strength Pareto Evolutionary Algorithm 2 (SPEA2) in MATLAB

Robust Ensemble-Based Evolutionary Calibration of SWAN model

Genetic algorithm optimization based on SPEA2

Genetic policy optimiser for specific environments using cellular automata

An implementation of most used multi-objective algorithms using jmetal in python.

Mirror - Genetics Algorithms and Genetic Programming library. https://genetics4j.org

Tese de conclusão de Curso

Header-only, generic C++14 implementation of the SPEA2 algorithm