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Multi-Objective Optimization Method for Dynamic Scheduling in 3D Printing Based on Improved NSGA-II

Longkun Luo, Liang Guo, Lixu Mou
Vol. 8, No. 3, pp. 154-163, 2026 DOI: 10.54691/9ddhs704 March 22, 2026
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Abstract.To address unreasonable scheduling in distributed 3D printing systems under dynamic disturbances, an event-driven multi-objective dynamic scheduling optimization method is proposed. First, a model minimizing makespan and total processing cost is constructed, defining disturbance triggers and rescheduling criteria. Second, an improved NSGA-II algorithm is designed, featuring a chromosome segmentation mechanism to coordinate local and global optimization, adaptive operators for convergence efficiency, and a cost-aware greedy mutation strategy to enhance solution quality. Simulations show that, compared to traditional right-shift rescheduling, the proposed method significantly reduces makespan and slightly lowers total cost in equipment failure scenarios, offering an efficient solution for cloud manufacturing platforms.
Keywords. 3D Printing; Dynamic Scheduling; Multi-Objective Optimization; NSGA-II.
APA Citation Longkun Luo, Liang Guo, Lixu Mou (2026). Multi-Objective Optimization Method for Dynamic Scheduling in 3D Printing Based on Improved NSGA-II. Scientific Journal of Technology, 8(3), 154-163. https://doi.org/10.54691/9ddhs704

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