Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems // Provides tools for general- purpose continuous optimization and feed-forward artificial neural network training using metaheuristic and gradient-based optimization algorithms. The package supports benchmark function optimization, regression, binary classification, and multi-class classification with multilayer perceptrons. The package implements several optimization methods, including particle swarm optimization Kennedy and Eberhart (1995) doi:10.1109/ICNN.1995.488968, differential evolution Storn and Price (1997) doi:10.1023/A:1008202821328, grey wolf optimizer Mirjalili et al. (2014) doi:10.1016/j.advengsoft.2013.12.007, secretary bird optimization Fu et al. (2024) doi:10.1007/s10462-024-10729-y, and Adam Kingma and Ba (2015) doi:10.48550/arXiv.1412.6980.