TESO Tabu Enhanced Simulation Optimization for Noisy Black Box Problems

This article likely presents a novel optimization algorithm, TESO, designed to tackle complex optimization problems where the objective function is unknown (black box) and the data is noisy. The use of 'Tabu' suggests a metaheuristic approach, possibly incorporating techniques to avoid getting stuck in local optima. The focus on simulation optimization implies the algorithm is intended for scenarios involving simulations, which are often computationally expensive and prone to noise. The ArXiv source indicates this is a research paper.