CAD-Designer Inspired Optimization Algorithm

CAD designers demonstrate unique design thinking and strategies during engineering modeling, such as modular decomposition, constraint prioritization, and iterative refinement. These behaviors have potential heuristic value in optimization problems. This paper proposes a CAD-Designer Inspired Optimization Algorithm (CAD-DOA). By emulating the designer's modular thinking, constraint-driven adjustment, and module dependency reconciliation mechanism, this algorithm enables the search and solution of complex, high-dimensional optimization problems. Based on the algorithm's design philosophy, this paper establishes a comprehensive mathematical model and proposes three innovative mechanisms: multi-scale module iteration, constraint-driven random perturbation, and module dependency reconciliation. The algorithm's update formulas, constraint handling mechanism, and module collaboration strategy are all described in detail using plain text mathematical formulas, providing a novel theoretical approach for high-dimensional optimization problems.