An intelligent algorithm integrated with fit algorithms for solving the one-dimensional bin packing problem under multiple length restrictions

Abstract

The purpose of cutting material to length is to cut the material into finished products according to customer needs and minimize the amount of surplus material. To address this problem, we propose a model for extensions to the one-dimensional bin packing problem involving multiple length restrictions, which considers that all finished products have different lengths, and all length requirements are loaded into the finished products to achieve the optimization objectives of minimizing the quantity of the finished material and minimizing the remaining length of the finished material. The model is solved by a hybrid intelligent algorithm consisting of a genetic algorithm integrated with fit algorithms. The effectiveness of the hybrid intelligent algorithm is theoretically validated and experimentally verified using actual data and specific numerical examples.