مدلی جهت بهینه سازی عملکرد پردازش اطلاعات در زنجیره تأمین مجازی، مبتنی بر اینترنت اشیا (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
امروزه، صنعت تولید با گسترش محدودیت های فیزیکی تجارت در سطح جهان، فناوری های مدرن اطلاعاتی را به منظور بهینه سازی روند تجارت و دستیابی به ادغام با شرکای زنجیره تأمین در پیش گرفته است که ازنظر جغرافیایی پراکنده اند. مدل های سنتی زنجیره تأمین، توجه اصلی را به بهینه سازی جریان های فیزیکی می دهد؛ با وجود این، اطمینان از اینکه واحدهای فیزیکی قابلیت پردازش اطلاعات مناسب را دارد نیز به همان اندازه مهم است. به این منظور در این پژوهش، بهینه سازی عملکرد پردازش اطلاعات در زنجیره تأمین مجازی حلقه بسته، با هدف حداکثرسازی سود و سرعت پردازش اطلاعات، با در نظر گرفتن هزینه های مجازی، امنیت اطلاعات و مصرف انرژی بررسی شده است. مدل برنامه ریزی خطی نهایی با استفاده از الگوریتم های فراابتکاری نسخه دوم الگوریتم ژنتیک، با مرتب سازی نامغلوب (NSGA-II) و نسخه دوم، مبتنی بر قوت پارتو (SPEA-II) بهینه سازی شده است. نتایج حل مدل با استفاده از الگوریتم های NSGA-II و SPEA-II، سود زنجیره تأمین مجازی را به ترتیب 106×93/9 و 106×23/4 و سرعت پردازش اطلاعات را به ترتیب 48/337 و 07/94 واحد نشان داد. به این ترتیب، الگوریتم NSGA-II در سودسازی زنجیره تأمین عملکرد بهتری دارد.A model for the optimization of information process performance in the IoT-based virtual supply chain
Purpose: Today, the manufacturing industry, with the expansion of the physical constraints of trade worldwide, has adopted modern information technologies to optimize the business process and achieve integration with geographically dispersed supply chain partners. Traditional supply chain models focus on optimizing physical flows. However, it is equally important to ensure that physical units can process appropriate information. This paper aims to propose a model for the optimization of information process performance in the IoT-based virtual supply chain. Design/methodology/approach: In this study, information processing performance in the closed-loop virtual supply chain has been optimized to maximize profit and information processing speed by considering costs of virtual, information security, and energy consumption. The final programming model has been optimized using meta-heuristic algorithms, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and the Strength Pareto Evolutionary Algorithm (SPEA-II). Findings – The results indicated that there is an inverse relationship between virtual supply chain profit and information processing speed (delay). The results of model solving using NSGA-II and SPEA-II algorithms underlined the virtual supply chain profit of 9.93×106 and 4.23×106, and the data processing speed of 337.48 and 94.07, respectively. Thus, the NSGA-II algorithm contributes more to the supply chain profitability. Research limitations/implications - The proposed model can be used in manufacturing industries equipped with IoT. Unavailability of practical examples and insufficient data are the two main limitations of the study. Practical implications:- The proposed model improves the production process and helps managers to plan better for their supply chain management and make timely decisions by sharing information across the supply chain and being aware of the flows of products and associated parts. Social implications - The Internet of Things in the virtual supply chain provides an opportunity to manage logistics systems and results in efficient online delivery with minimal cost. The information flow integrates all links and participants in the virtual supply chain. It enables each member to obtain the accurate information needed for logistics capability, reduces resource wastage, and improves customer satisfaction. Originality/value: One of the innovative aspects of this research is the use of IoT in the virtual supply chain for the integration and transparency of information in the supply chain, considering the importance of information in the virtual supply chain and examining the impact of IoT usage on closed-loop virtual supply costs and target functions. In addition to considering the physical flow costs of the closed-loop, including production costs, separation costs, repair, disposal, recycling, etc., in the cost objective function, virtual flow costs included IoT usage costs and information security costs. Energy consumption was also included in the objective function. Also, due to the virtualization of the supply chain and the significant role of information, optimization of information processing speed was considered in modeling the supply chain performance, which is another innovative aspect of research.
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