مدلی جهت بهینه‌سازی عملکرد پردازش اطلاعات در زنجیرۀ تامین مجازی، مبتنی بر اینترنت اشیا

امروزه، صنعت تولید با گسترش محدودیت‌های فیزیکی تجارت در سطح جهان، فناوری‌های مدرن اطلاعاتی را به‌منظور بهینه‌سازی روند تجارت و دستیابی به ادغام با شرکای زنجیرۀ تامین در پیش گرفته است که ازنظر جغرافیایی پراکنده‌اند. مدل‌های سنتی زنجیرۀ تامین، توجه اصلی را به بهینه‌سازی جریان‌های فیزیکی می‌دهد؛ 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، بهینه‌سازی عملکرد پردازش اطلاعات در زنجیرۀ تامین مجازی حلقۀ بسته، با هدف حداکثرسازی سود و سرعت پردازش اطلاعات، با در نظر گرفتن هزینه‌های مجازی، امنیت اطلاعات و مصرف انرژی بررسی شده است. مدل برنامه‌ریزی خطی نهایی با استفاده از الگوریتم‌های فراابتکاری نسخۀ دوم الگوریتم ژنتیک، با مرتب‌سازی نامغلوب (nsgaii) و نسخۀ دوم، مبتنی بر قوت پارتو (speaii) بهینه‌سازی شده است. نتایج حل مدل با استفاده از الگوریتم‌های  nsgaii و speaii، سود زنجیرۀ تامین مجازی را به‌ترتیب 106×9.93 و 106×4.23 و سرعت پردازش اطلاعات را به‌ترتیب 337.48 و 94.07 واحد نشان داد. به این ترتیب، الگوریتم nsgaii در سودسازی زنجیرۀ تامین عملکرد بهتری دارد.

A model for the optimization of information process performance in the IoTbased 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 IoTbased virtual supply chain. Design/methodology/approach: In this study, information processing performance in the closedloop 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 metaheuristic algorithms, the NonDominated Sorting Genetic Algorithm II (NSGAII), and the Strength Pareto Evolutionary Algorithm (SPEAII).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 NSGAII and SPEAII 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 NSGAII 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 closedloop virtual supply costs and target functions. In addition to considering the physical flow costs of the closedloop, 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.