StarPSO: A Unified Framework for Particle Swarm Optimization Across Multiple Problem Types

StarPSO is an open source, object-oriented, Python library designed to implement various particle swarm optimization (PSO) algorithms, including: (i) StandardPSO, (ii) BinaryPSO, (iii) IntegerPSO, (iv) QuantumPSO, (v) CategoricalPSO, (vi) BareBonesPSO, and (vii) JackOfAllTradesPSO (for mixed variable type problems). This library addresses the challenge of optimizing diverse problem types through a unified framework. Implemented with performance optimizations using NumPy, Numba, and Joblib, it achieves efficient computation while preserving clean, well-documented, and maintainable code. Provided in a public GitHub repository, StarPSO encourages reuse and collaboration, allowing researchers and practitioners to easily integrate advanced optimization techniques into their own projects and benefit a wide range of applications across different domains.