Identifying and determining the priority of financial supply chain optimization indicators for production improvement with using Hopfield artificial neural network
سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 96
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شناسه ملی سند علمی:
JR_IJFMA-10-36_020
تاریخ نمایه سازی: 17 دی 1402
چکیده مقاله:
Finding the relationship between the components of the financing chain and improving the performance of the production cycle requires identifying the gaps and gaps between these two important categories. In the current research, it was tried to first take the basic steps to identify these gaps, then formulate them to optimize the financing chain to improve production. After building and solving the model, it was implemented through mathematical algorithms and relevant software, and then a multi-objective problem was designed to analyze the results and compare each of the components. Using them, the output of the algorithm was analyzed as a result. Finally, to check the validity of the findings, an interview was conducted with the managers and experts of the production units and the results were applied in making decisions to provide mathematical and computational planning. The qualitative part of the research was also conducted using the opinions of managers of manufacturing companies and experts and professors in production and financial management. The statistical population in the quantitative part of the research is all the machinery and equipment industry companies accepted in the Tehran Stock Exchange, out of ۲۰ companies,۱۷ active companies were considered. The results showed that the development of supply chain financial resources brings a new incentive for companies and society. In general, this research studies a model of the relationship between the financing chain and the production cycle and finally shows what factors can improve and promote the production cycle and can affect the performance of companies.
کلیدواژه ها:
Optimization ، Financing chain ، Improvement of the production performance cycle ، Artificial Neural Network
نویسندگان
Reyhaneh Ziloochi
Ph.D Student, Department of Industrial management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Mohammad Ebrahim Mohammad Pourzarandi
Professor, Department of Industrial management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
zadallah fathi
Associate Professor of Accounting Department of Acconting, Tehran Branch, Islamic Azad University, Tehran, Iran
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