population-based-optimization

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

[JMLR (CCF-A)] PyPop7: A Pure-PYthon LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* algorithm variants. In the near future, we will add Learning-Based Optimizers as its extensions. [https://jmlr.org/papers/v25/23-0386.html]

A ray-based library of Distributed POPulation-based OPtimization for Large-Scale Black-Box Optimization.

A data-driven initialization to population-based search strategies

A pure-MATLAB library for POPulation-based Large-Scale Black-Box Optimization (pop-lsbbo).

Orama NAS Codebase: a modular framework for composing and evaluating neural architecture search strategies from interchangeable components (selection, crossover, mutation, variation, replacement, termination, and evaluation), operating on a dataset issued by merging NAS-Bench-201 and HW-NAS-Bench to optimize accuracy-latency trade-offs.

An implementation of the new Slime Mold Algorithm, a heuristic optimization technique, in combination with filter/statistical fitness functions for selecting the best subset of features from text datasets.

EvoScope: see what every operator of your population-based optimizer does. Numerical checks of new operators, attribution of performance to operators, algorithm-level diagnostics and discovery guarantees for evolution strategies, genetic algorithms, and swarm and consensus methods.