Simulated Annealing GUI Demonstration

This demonstration utilizes a graphical user interface (GUI) to showcase the simulated annealing algorithm for solving global optimization problems. The implementation features temperature scheduling controls, solution space visualization, and real-time progress tracking. Key algorithmic components include neighbor solution generation through random perturbations, acceptance probability calculation using the Metropolis criterion (exp(-ΔE/T)), and exponential cooling schedules. Users can interactively adjust parameters such as initial temperature, cooling rate, and iteration count while observing the algorithm's convergence behavior. The demonstration covers essential phases: initial solution generation, iterative improvement through probabilistic acceptance of worse solutions to escape local optima, and final convergence to global optimum. This visualization helps users understand the algorithm's balance between exploration and exploitation, making it suitable for studying complex optimization landscapes and practical implementation techniques.