Construction of e-commerce system based on 5G and Internet of Things technology

In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the Internet of Things technology to improve the e-commerce system, and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the Internet of Things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system, and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and Internet of Things technology constructed in this paper is very reliable.

Enhancing Competitive Capabilities of Healthcare SCM through the Blockchain: Big Data Business Model’s Viewpoint

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

Research on Automation Control of University Logistics Management System Based on Wireless Communication Network

Nowadays, individuals with and without technical knowledge have started utilizing the technology to a broader extent. The utilization of technology has gone deeper concerning gadgets that aid in wireless communication with anyone or anything. This advancement has paved the way for a trending technology named wireless communication network (WCN) in recent years. In addition to this, there has been a significant change and development in the field of trading goods. Manual ordering of goods has changed to online ordering, and hence, supply chain management. This research focuses on applying WCN to a logistic tracking information system (LTIS) for a university with automatic control of the system. A novel algorithm named intelligent logistics system construction algorithm is implemented to evaluate the efficiency and performance of data. This model aids in the tracking goods and automatic control of university logistics.

Demand Forecast on the Orchard Cold Chain Logistics in Hunan Province Based on Cognitive Neuroscience

How to scientifically and effectively predict the cold chain logistics demand and provide basis for decision making has always been the focus of forestry and orchard logistics research. From the learning environment of neurons, cognitive neuroscience provides a new perspective for forecasting the demand for cold chain logistics. This paper uses the cognitive neuroscience theory to construct a BP neural network model containing two hidden layers to predict the cold chain logistics demand of the forestry and orchard industry in Hunan province in 2017-2021. Suggestions are then given from the aspects of cold chain logistics construction, transportation infrastructure construction, government policy, enterprise and industry according to the prediction results, thus, providing a theoretical basis for the planning of the cold chain logistics system of Hunan province in a certain period of time, as well as references for the development of cold chain logistics in other parts of the country.

Demand Forecast on the Orchard Cold Chain Logistics in Hunan Province Based on Cognitive Neuroscience

How to scientifically and effectively predict the cold chain logistics demand and provide basis for decision making has always been the focus of forestry and orchard logistics research. From the learning environment of neurons, cognitive neuroscience provides a new perspective for forecasting the demand for cold chain logistics. This paper uses the cognitive neuroscience theory to construct a BP neural network model containing two hidden layers to predict the cold chain logistics demand of the forestry and orchard industry in Hunan province in 2017-2021. Suggestions are then given from the aspects of cold chain logistics construction, transportation infrastructure construction, government policy, enterprise and industry according to the prediction results, thus, providing a theoretical basis for the planning of the cold chain logistics system of Hunan province in a certain period of time, as well as references for the development of cold chain logistics in other parts of the country.

Design of Prototype Information System for Tracking & Tracing Fish Distribution Based on Mobile Agent

The National Fish Logistics System or often called SLIN is an Indonesian Ministry of Maritime Affairs and Fisheries program that aims to maintain the stability of the production and marketing systems and control the disparity in national fish prices. Central Sulawesi is the Province that becomes the main corridor of this program. The inefficient distribution monitoring process generally causes several problems in the field of fisheries distribution management that still often occur today by the regional Ministry of Maritime Affairs and Fisheries. It indicates that SLIN is not yet running optimally. This study purpose a prototype design of fish distribution tracking based on a mobile agent that can use to help consumers to track distribution channels and get information about the origin of the fish to be purchased. The data will further process for monitoring fish distribution in a real-time manner by the regional Ministry of Maritime Affairs and Fisheries. A proper monitoring mechanism will undoubtedly help the government in making policies and conducting supervision to make the SLIN implementation successful in Central Sulawesi. By the research, we found that the proposed method can gather data from every level fish distribution agent then processed the data to inform about distribution line and the origin of the fish for the consumer. The proposed solution framework could be implemented and nearly fit with current implementation criteria. The framework later can be a base framework for developing a more advanced information system for SLIN in Central Sulawesi Region.

Simulation optimization of an inventory control model for a reverse logistics system

Nowadays, companies are recognizing their primordial roles and responsibilities towards the protection of the environment and save the natural resources. They are focusing on some contemporary activities such as Reverse Logistics which is economically and environmentally viable. However, the integration of such an initiative needs flows restructuring and supply chain management in order to increase sustainability and maximize profits. Under this background, this paper addresses an inventory control model for a reverse logistics system that deals with two separated types of demand, for new products and remanufactured products, with different selling prices. The model consists of a single shared machine between production and remanufacturing operations, while the machine is subject to random failures and repairs. Three stock points respectively for returns, new products and remanufactured products are investigated. Meanwhile, in this paper, a modeling of the problem with Discrete-Event simulation using Arena® was conducted. Regarding the purpose of finding, a near-optimal inventory control policy that minimizes the total cost, an optimization of the model based on Tabu Search and Genetic Algorithms was established. Computational examples and sensitivity analysis were performed in order to compare the results and the robustness of each proposed algorithm. Then the results of the two methods were compared with those of OptQuest® optimization tool.

Logistics support planning model in the conditions of limited resources

Introduction/purpose: The paper presents a model of logistics support planning in the conditions of limited logistic resources based on the prioritization of customer requirements and resource allocation. Decisionmakers play a crucial role in the efficient and equitable allocation of resources as they prioritize among different user requirements. Methods: Requirement prioritization techniques that use nominal scale, ordinal scale, and ratio scale, and five methods for converting ranks into weighting coefficients have been applied to determine the degree of significance of user requirements. The Requirements triage method has been used for establishing relative priorities, while the heuristic algorithm determining the Kemeny median was used to consolidate individually ranked requests into a group rank. In order to balance opposing demands of users, consensus measures of group decision making were used. For obtaining an optimal planned solution of logistic support, the methods and techniques of resource allocation were applied. Results: A model for adaptive planning of logistics support in the conditions of limited resource capacities of the logistics system has been developed. Conclusion: The proposed model can be effectively applied in other areas of resource allocation.

Study of integral logistics in a geological and petrographic laboratory, in the southeast region of Mexico, for the proposal of an integral model

For organizations to have the growth that the global economy demands, they must bet on improvement alternatives that fully involve the entire system. One of these alternatives is to bet on the improvement of integral logistics, since it serves as a connection between production and markets. This research proposes the generation of a model for the improvement of the logistics system in a geological and petrographic laboratory, in the southeaster region of Mexico, with the sole purpose of adding value and providing alternative solutions to current or future problems that arise. It is also proposed to design an instrument that measures the current situation in logistics and provides a comprehensive scenario that serves as a starting point for improvement strategies. This instrument is created tailored to the company and introduces intangible aspects called factors so that with the help of the Likert scale they are transformed into qualitative values, and thus carefully visualize the study problem. The entire study is analysed and interpreted by the researcher, and with the help of the company's experts, it is considered to obtain reliable and secure information.