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<p>The cloud manufacturing model plays a crucial role in the deep integration of information technology and the manufacturing industry. However, it is challenging to select the optimal service resources for production when the relationships among multiple manufacturing objectives and the intrinsic connections between service resources and industrial production constraints are not fully considered in the manufacturing process. Therefore, this paper constructs a service selection optimization model with multiple production constraints in a cloud manufacturing environment. In addition, this paper proposes an innovative moth optimization algorithm based on a multi-objective non-dominant solution to improve the effectiveness of the selection process. Experimental study demonstrates that the proposed method achieves a 15% improvement in solution quality and resource utilization increased by 20.38% compared to some widely used baseline methods, helping enterprises make efficient use of resources and enhance service competitiveness.</p>

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A multi-objective pareto optimization service selection approach considering cloud manufacturing production constraints

  • 期刊论文

  • 发表日期：

    2025年8月19日

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  • Xiubao Zheng,
  • Jing Li,
  • Ming Zhu,
  • Jie Dai

摘要

The cloud manufacturing model plays a crucial role in the deep integration of information technology and the manufacturing industry. However, it is challenging to select the optimal service resources for production when the relationships among multiple manufacturing objectives and the intrinsic connections between service resources and industrial production constraints are not fully considered in the manufacturing process. Therefore, this paper constructs a service selection optimization model with multiple production constraints in a cloud manufacturing environment. In addition, this paper proposes an innovative moth optimization algorithm based on a multi-objective non-dominant solution to improve the effectiveness of the selection process. Experimental study demonstrates that the proposed method achieves a 15% improvement in solution quality and resource utilization increased by 20.38% compared to some widely used baseline methods, helping enterprises make efficient use of resources and enhance service competitiveness.