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Managing the risk of supply chain bankruptcy in supply chain network redesign

机译:管理供应链网络重新设计供应链破产风险

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All vital operations of a supply chain network (SCN) are inherently affected by uncertainties and risks in the economic environment. In this study, we extend an existing SCN model by elaborating on stochastic price and demand, and integrating economic uncertainty. Financial performance and credit solvency are of utmost importance when analysing the financial status of an SCN. Each of these components focuses on a different aspect of investment attractiveness under various economic conditions, and in turn, facilitates access to capital for the companies involved. We extend the SCN model with financial performance optimisation approach to a novel model to include the trade-offs between two objective functions: (1) the total equity as the financial performance of the SC, and (2) the Altman’s Z-score as the credit solvency factor of the company. The model ascertains the future profitability, leverage, and liquidity of the SC by determining the optimal levels of production and inventory in each facility of the new network design. We introduce a weighted sum method and a novel genetic algorithm (GA) solution approach to solve the resultant bi-objective mixed integer nonlinear programming problem. We illustrate the representation scheme required for the GA in this paper.
机译:供应链网络(SCN)的所有重要操作都通过固有的经济环境的不确定性和风险的影响。在这项研究中,我们通过详细阐述了随机价格和需求,并整合经济的不确定性扩展现有的SCN模式。分析的SCN的财务状况时,财务业绩和信用偿付能力是非常重要的。每个组件都集中于投资吸引力的各种经济条件下的不同方面,而反过来,有利于获得资金所涉及的公司。我们与财务绩效优化方法的SCN模式扩展到一个新的模式,包括了两个目标函数之间的权衡:(1)总股本为SC的财务表现,和(2)的奥特曼的Z分数为该公司的信用偿付能力的因素。该模型通过确定新的网络设计的各个工厂生产和库存的最佳水平查明未来的盈利能力,杠杆率和SC的流动性。我们引入一个加权和方法和一种新的遗传算法(GA)溶液的方法来解决所得到的双目标混合整数非线性规划问题。我们说明本文的GA所需的表示方法。

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