18 Test Function Programs for Intelligent Optimization Algorithms

This documentation presents a comprehensive set of 18 test function programs implemented in MATLAB for assessing intelligent optimization algorithms. These test functions serve as benchmark tools to evaluate algorithm performance, convergence behavior, and solution quality across various optimization scenarios. The collection includes implementations of different optimization strategies and heuristic approaches, featuring key MATLAB functions such as objective function definitions, constraint handling mechanisms, and solution evaluation metrics. These algorithms are designed to address diverse problem domains including numerical optimization, search space exploration, parameter tuning, and multi-objective optimization scenarios. Each test function incorporates specific mathematical formulations and evaluation criteria, implemented through MATLAB's optimization toolbox functions and custom algorithmic structures. The programs utilize MATLAB's matrix operations and function handles for efficient computation, with implementations covering gradient-based methods, population-based algorithms, and hybrid optimization techniques. This test suite provides researchers and developers with essential tools for comparative analysis, algorithm validation, and performance benchmarking in intelligent optimization research, offering critical insights into algorithm efficiency, robustness, and solution quality through standardized testing procedures.