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Modeling of Biological Intelligence for SCM System Optimization

机译:SCM系统优化的生物智能建模

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摘要

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.
机译:本文总结了生物智能中用于建模和优化供应链管理(SCM)系统的一些方法,包括遗传算法,进化规划,差异进化,群体智能,人工免疫以及其他与生物智能相关的方法。 SCM系统是自适应的,动态的,开放的自组织,由信息,物料,货物,资金和能源的流动来维持。用于建模和优化复杂SCM系统的传统方法需要大量的计算资源,而基于生物智能的解决方案通常可以提供有效解决问题的有价值的替代方法。本文总结了最近有关SCM系统设计和优化的方法,涵盖了应用最广泛的遗传算法和其他进化算法。

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