考虑多材料和二维装箱的3D打印调度问题研究OA

With the development of 3D printing technology in the direction of multi-material,the dual constraints of material con-version and 2D space optimization of the build platform are derived,which significantly increase the complexity of production scheduling.In order to meet this challenge,with the optimization objective of minimizing the total latency time of all parts,a math-ematical model was established by combining the multi-material and 2D packing constraints,and an improved genetic algorithm was proposed to solve it.In particular,it newly designed the corresponding coding and initialization methods to support the gener-ation of high-quality feasible solutions under complex constraints.Moreover,it considered the horizontal rotation of the part in the bottom-left heuristic algorithm in order to explore the 2D packing problem.It also integrated elitism method and Boltzmann selec-tion to design a new hybrid selection strategy.Additionally,new crossover and mutation strategies were constructed to balance the exploration and exploitation capabilities of the algorithm.Finally,the experimental results show that the proposed algorithm is ef-fective and robust in obtaining high-quality solutions in different sizes of experiments,and also exhibits excellent performance in comparison with other genetic algorithms.