ACP-MO: A NOVEL METAHEURISTIC OPTIMIZATION ALGORITHM BASED ON AN ADVANCED CERAMIC PROCESSING METAPHOR FOR OPTIMIZATION

In the field of modern optimization, heuristic algorithms are widely used in various optimization tasks due to their excellent performance on complex problems. This paper proposes a new heuristic optimization algorithm, the Advanced Ceramic Process Heuristic Optimization Algorithm (ACP-MO). Inspired by the ceramic machining process, the algorithm uses forming operations and reverse design repair strategies to simulate the dynamic process in ceramic machining. By optimizing 10 typical test functions, the experimental results show that ACP-MO outperforms multiple common algorithms in terms of optimization accuracy. ACP-MO refers to the three- stage optimization process of the advanced ceramic manufacturing process, which includes the forming stage, sintering stage and repair stage. These three stages correspond to exploration, quality assessment and local refinement, respectively. A new integration of temperature control convergence, Gaussian perturbation and inverse design heuristic correction mechanism is introduced, which provides a new perspective for the design and development of meta-heuristic algorithms.