Knowledge-Assisted Optimization for Large-Scale Design Problems: A Review and Proposition

摘要

Practicing design engineers often have certain knowledge about a design problem. However, in the last decades, the design optimization community largely treats design functions as black-boxes. This paper discusses whether and how knowledge can help with optimization, especially for large-scale optimization problems. Existing large-scale optimization methods based on black-box functions are first reviewed, and the drawbacks of those methods are briefly discussed. To understand what knowledge is and what kinds of knowledge can be obtained and applied in a design, the concepts of knowledge in both artificial intelligence (AI) and in the area of the product design are reviewed. Existing applications of knowledge in optimization are reviewed and categorized. Potential applications of knowledge for optimization are discussed in more detail, in hope to identify possible directions for future research in knowledge-assisted optimization (KAO).