The Clustering NIGA for Solving the Nesting Problem in the Hull Construction Automatic Nesting System

Abstract

For improving the nesting efficiency, the clustering idea and algorithm are introduced and the effective characteristics of matching nesting-graphics are extracted and analyzed. The paper discusses the irregular parts nesting problem based on an improved immune genetic algorithm, and a NIGA based on crowing mechanism is proposed. GA, an improved immune genetic algorithm, and NIGA are applied to practical experiments respectively to solve the nesting problem and optimize the results, and we compare the results. In solving the large-scale nesting problem, the application of immunity operator and niche genetic algorithm based on crowing mechanism improves the global optimization performance and velocity of convergence. The improved algorithms based on the clustering idea are effective and feasibility for solving the hull construction automatic nesting problem.