Data Fitting for <i>k</i>_<i>ij</i> − c_<i>ij</i>.

The Graphical Evaluation and Review Technique (GERT) and complex networks are used to simulate and analyse complex product supply chain networks based on the characteristics of complex product supply chain networks. And the traditional GERT is improved by constructing a grey parametric GERT network with restricted output results, taking into account the fact that the duration, product quality and product cost of each supplier in a complex product supply chain are interval values rather than definite values, and that customers have restrictions on the duration, product quality and product cost of the final product. The functional relationship between product quality, product cost and duration is analysed, and two satisfaction functions for duration and cost are constructed in order to quantify the multi-objective requirements of shortening duration, saving product cost and guaranteeing product quality for complex products under emergency situations. Then, a duration-cost-quality model for complex product supply chains in contingency situations is constructed to obtain the better duration, product cost and product quality of each supplier by optimising the indicator parameters in the network. Finally, the scientific validity and effectiveness of the model and method are verified by means of arithmetic example. The results show that the method is able to analyse the optimal duration, product quality and product cost of each supplier, and the main manufacturer can obtain an optimised combination of duration, cost and quality for a complex product supply chain in different contingency situation. To further promote the sustainable and secure development of complex product supply chains, this paper also suggests the integration of data sharing and blockchain technology with complex product supply chains to develop dynamic supply chain feedback management systems.本文采用图形评审技术（Graphical Evaluation and Review Technique，GERT）与复杂网络，基于复杂产品供应链网络的特性对该类供应链网络进行模拟与分析。考虑到复杂产品供应链中各供应商的工期、产品质量与成本均为区间值而非确定值，且客户对最终产品的工期、质量与成本存在约束，本文通过构建带受限输出结果的灰色参数化GERT网络，对传统GERT进行改进。本文分析了产品质量、成本与工期间的函数关系，同时构建工期与成本两类满意度函数，以量化应急场景下复杂产品对缩短工期、节约成本与保障质量的多目标需求。随后，本文构建了应急场景下复杂产品供应链的工期-成本-质量模型，通过优化网络中的指标参数，得到各供应商的最优工期、产品成本与产品质量。最后，本文通过算例验证了该模型与方法的科学性、有效性与可行性。结果表明，该方法可实现各供应商最优工期、产品质量与产品成本的分析，且主制造商可获取不同应急场景下复杂产品供应链的工期、成本与质量优化组合方案。为进一步推动复杂产品供应链的可持续与安全发展，本文还提出将数据共享与区块链技术融入复杂产品供应链，以构建动态供应链反馈管理系统。