مرور نظام‌مند کاربردهای شبکه عصبی مصنوعی در مدیریت زنجیره تأمین
محورهای موضوعی : مدیریت صنعتیسید مجتبی حسینی بامکان 1 * , عارف طغرالجردی 2 , پوریا مالکی نژاد 3
1 - دانشگاه یزد
2 - دانشگاه یزد
3 - دانشگاه یزد
کلید واژه: شبکه های عصبی, زنجیره تامین, انتخاب تامین کننده, طراحی لجستیک,
چکیده مقاله :
معیار موفقیت شرکت‌ها و سازمان‌ها در بازار رقابتی امروز عملکرد زنجیره تأمین شرکت هاست. به منظور بهبود عملکرد زنجیره تأمین شرکت‌ها و موفقیت آنها تاکنون از روش‌ها و تکنیک‌های مختلفی استفاده شده است. یکی از روش‌های پرکاربرد در زمنیه حل این معضلات، شبکه عصبی مصنوعی است. هدف از این پژوهش مرور نظام‌مند کاربردهای مختلف شبکه‌های عصبی مصنوعی در حل معظلات و مشکلات بخش‌های مختلف زنجیره تأمین است. بدین منظور در ابتدا با استفاده از مرور ادبیات، واژگان کلیدی ارتباطی میان این دو حوزه شناسایی گردید. با استفاده از کلمات کلیدی استخراج شده از ادبیات پژوهش اقدام به جستجو در میان دو پایگاه داده اسکوپوس و وب آف ساینس گردید. با جستجو در این پایگاه داده‌ها مقالات مرتبط به کاربرد شبکه عصبی مصنوعی در حوزه‌های مختلف زنجیره تإمین استخراج گردید. در نهایت مقالات با استفاده از ابزارهای متعدد فیلتر و سپس مقالات دارای اهمیت بالا شناسایی گردید. با استفاده از مقالات مهم شناسایی شده، دسته‌بندی‌های مختلفی از کاربردهای شبکه عصبی مصنوعی در مدیریت زنجیره تأمین صورت پذیرفت. نتایج این پژوهش نشان می‌دهد شبکه‌های عصبی مصنوعی در حل مسائل مربوط به مهندسی، علوم کامپیوتر و کسب و کار و مدیریت بیشترین کاربرد را داشته است.
Nowadays, the success rate of companies/organizations in the competitive market is the performance of their supply chain managment. Various techniques have been utilized to improve it, which one of the most widely used methods to solve these problems is artificial neural network. The purpose of this study is to systematically review the various applications of artificial neural networks in solving the problems of different parts of the supply chain. Hence, by using the literature review, the key vocabulary of the link between the two domains was identified. Using the keywords extracted from the research literature, a search was made between the Scopus databases and Web-based Science. By searching in these databases, articles related to the application of artificial neural network in different areas of supply chain have been extracted. Finally, the articles were filtered using a variety of tools and then high-ranking papers were identified. Using important articles identified, various categories of artificial neural network applications were implemented in supply chain management. The results of this study indicate that artificial neural networks have been most used in solving engineering, computer science and business issues
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