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Joint duration-cost-quality optimization model for complex product supply chains under contingency conditions.

Yunzhe Li1, Peng Dong1, Weimin Ye1

  • 1Naval University of Engineering, Wuhan, China.

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Summary

This study enhances supply chain analysis using a grey parametric GERT network, optimizing duration, cost, and quality for complex products during emergencies. It provides a model for better supplier selection and supply chain management.

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Complex Systems Analysis

Background:

  • Complex product supply chains face challenges with variable supplier data (duration, quality, cost) and customer restrictions.
  • Traditional simulation methods struggle with the uncertainty and multi-objective nature of these supply chains, especially in contingency situations.

Purpose of the Study:

  • To develop an improved simulation and analysis method for complex product supply chains.
  • To construct a duration-cost-quality model for optimizing supply chain performance under contingency situations.
  • To quantify multi-objective requirements for duration, cost, and quality.

Main Methods:

  • Utilized Graphical Evaluation and Review Technique (GERT) and complex networks.
  • Developed a grey parametric GERT network accounting for interval values and customer restrictions.
  • Constructed satisfaction functions for duration and cost to address multi-objective requirements.
  • Optimized indicator parameters within the network to achieve better duration, cost, and quality.

Main Results:

  • The proposed model effectively analyzes optimal duration, product quality, and product cost for each supplier.
  • Main manufacturers can achieve optimized combinations of duration, cost, and quality for complex product supply chains in various contingency situations.
  • The method's scientific validity and effectiveness were verified through an arithmetic example.

Conclusions:

  • The developed grey parametric GERT model provides a robust framework for analyzing and optimizing complex product supply chains in contingency scenarios.
  • Integration with data sharing and blockchain technology is recommended for dynamic feedback management systems to enhance supply chain sustainability and security.