Solving NP-Hard Problems Using POS Algorithms

Here, we provide a detailed introduction to our program. Our solution employs POS (Problem Optimization Strategy) to address NP-hard problems, with a specific focus on solving the Traveling Salesman Problem (TSP). Through practical simulations and performance analysis, we have validated the rationality and feasibility of our algorithm. To achieve this, we developed a unique algorithmic framework that leverages POS techniques to tackle NP-hard challenges. The core implementation involves optimization heuristics that explore solution spaces efficiently, enabling the discovery of near-optimal solutions for problems previously deemed intractable by conventional methods. Key functions include dynamic path evaluation, cost minimization routines, and iterative refinement modules. The feasibility of our algorithm has been demonstrated across multiple real-world cases, including TSP instances and other NP-hard scenarios. We believe our approach will contribute to solving complex real-world problems by providing more effective computational strategies and enhanced solution quality.