Stochastic Contractive Descent (SCD) Algorithm: MATLAB Demo with Animated Visualization

This repository contains a MATLAB implementation of Stochastic Contractive Descent (SCD) algorithm, a novel population-driven metaheuristic optimization method. The demo features animated visualization of the algorithm's convergence process, showing initial population distribution, search space contraction, and final solution convergence. The code implements SCD's unique stochastic descent mechanism combined with progressive search space contraction, balancing exploration and exploitation. Includes visualizations of population movement trajectories, adaptive boundary adjustment, and convergence curve plotting. This demo accompanies the paper "Population-Driven Stochastic Contractive Descent for Complex Engineering Optimization Problems" and provides hands-on understanding of the SCD algorithm's mechanics through interactive 2D optimization examples. Keywords: metaheuristic optimization, stochastic optimization, population algorithm, MATLAB demo, engineering optimization, search space contraction, animated visualization