Tabu Search Optimizer

Tabu search is a metaheuristic that climbs a rugged optimization landscape using short-term memory instead of randomness: at each step it takes the best legal move in its neighborhood, forbids that move (and its near-reversals) from being repeated for a set number of iterations via a tabu list, and only breaks that rule when an aspiration criterion shows the forbidden move would set a new global best. This simulator renders a real 3D surface — Rastrigin, Ackley or Schwefel, all classic multimodal benchmark functions — and walks a search point across it live, coloring the neighborhood candidates that are currently tabu in red and tracking the best point found so far in green, so you can watch memory-based search escape local minima that a plain hill-climber gets stuck in.