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A Framework for Inventory Optimization Based on Machine Learning and Gamification in SMEs Manufacturing Sector

المصدر: مجلة التجارة والتمويل
الناشر: جامعة طنطا - كلية التجارة
المؤلف الرئيسي: Abd Elwahab, Marwa (Author)
مؤلفين آخرين: Al-Gazzar, Sara Hassan (Co-Author) , Mahar, Khaled Mohamed Mohammed (Co-Author) , Abdul Qader, Hatem Mohamed Said Ahmad (Co-Author)
المجلد/العدد: ع1
محكمة: نعم
الدولة: مصر
التاريخ الميلادي: 2024
الشهر: مارس
الصفحات: 117 - 135
ISSN: 1110-4716
رقم MD: 1479600
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EcoLink
مواضيع:
الشركات الصغيرة | التعلم المعزز | إدارة المخزون
كلمات المؤلف المفتاحية:
Reinforcement Learning | Inventory Management | Game Theory
رابط المحتوى:
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المستخلص: As supply chains strive for continuous improvements to maintain their strength and their ability to compete in the market. Optimization of different operational concepts and practices has become strategically vital. This importance increases dramatically in small to medium industries (SMEs) sector, which severely struggles to compete in the market due to managerial challenges. Accordingly, this research aims at developing a framework for inventory optimization in the SMEs manufacturing sector based on game theory, gamification, and multi-agent reinforcement learning simulation models. The game theory will be used to set strategies among different stakeholders within the supply chain; gamification is used to increase user motivation by applying game elements to a digital data collection system, while reinforcement learning techniques will be employed to set policies for inventory estimation in terms of reorder point, inventory ordering cost, and inventory level, upon which inventory optimization can be achieved. This paper conducts a systematic review of inventory optimization, highlights some limitations of current approaches and then concludes with the proposed framework to overcome these limitations. The systematic review revealed that there is no comprehensive framework for inventory optimization in the SMEs manufacturing sector, using "Reinforcement Learning and Game theory techniques". Practitioners can benefit from this model to optimize their inventory and make corrective actions considering inventory management system, particularly in SMEs.
ISSN: 1110-4716

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