Research on Stability of Optimal Sheet-cutting Strategy Based on Improved Real-Coded Genetic Algorithm

Abstract

With the increasing advancement of automation, the demand for efficient and versatile sheet-cutting optimization solutions is imperative. In this paper, the real-coded genetic algorithm is employed as the core algorithm to realize the automatic planning system for cutting two-dimensional plates combined with the actual requirement. According to the practical investigation in the building materials market, a certain type of sheet material and the final product model is simulated from the perspective of various requirements in this paper, in which the utilization rates and suppliers’ profits are also calculated and predicted to implement the effectiveness and advancement of the algorithm. The results show that compared with other methods, the optimal sheet-cutting strategy based on improved real-coded genetic algorithm reduces the computational complexity and maintains high stability under the premise of high utilization, which is more appropriate for systems with various product types and quantity constraints.