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With the advent of artificial intelligence and big data era, the application scenarios of smart transportation are becoming more and more extensive, and the transportation industry is also undergoing intelligent upgrades. According to the flexible customization requirements of Intelligent Traffic Cloud Platform business function, this paper presents a flexible customization of User Identity, which has been applied to a specific business system. Intelligent Traffic Cloud Platform as a new information processing infrastructure model and business model has been widely recognized. The model-driven strategy based on user identity uses the C# delegation mechanism. The storage of business function customization designs the driving strategy of flexible customization model and realizes the flexible customization of platform. This paper uses Load Runner v8.1, an industry-standard load-testing tool that predicts system behavior and performance, to predict system behavior and optimize system performance. Finally, the feasibility and effectiveness of the proposed scheme is verified by a specific service function on the Intelligent Traffic Cloud Platform.

Product-Service System (PSS) models offer an integrated service solution to create value for businesses. In the high-value manufacturing sector, value creation for maintaining market competitiveness and improving customer satisfaction is a challenging task. Designing an effective PSS solution depends on integrated service, and product requirements and constraints. Thereby, PSS contract decisions can be significantly influenced by customers' requirements, and also product and service features. However, existing literature primarily focuses on the impact of service requirements on the PSS contract decisions. Moreover, the existing insights for PSS customization mainly consider hysteretic customer requirements rather than forecasting the requirements under product and service uncertainties. In this paper, an agent-based cost-benefit analysis simulation model is implemented for the PSS contract decisions context. Moreover, a sensitivity analysis is conducted on service costs. Additionally, the effect of product remaining life on service contract decisions is analyzed. The simulation model considers stochastic uncertainty to study PSS contracts customization. The presented model supports PSS customization process by providing a quantitative tool that measures contracts' profitability as early as the requirement elicitation phase. Furthermore, the bottom-up nature of the model, and the integration of probabilistic uncertainties enhance the flexibility of PSS customization. A case study of PSS contract decision in the machine tool industry is considered for assessing the validity of the presented model. Studies on different forms of service uncertainty highlight that the product failure rate has the most influence on the profitability of a service contract. Moreover, the impact of product age on profitability in an availability-based contract is more significant compared to a spare-parts contract. [ABSTRACT FROM AUTHOR]

We consider a production planning problem of an assembly item, where each component of the item has several different versions. In flexible customization, rather than specifying only one version for each component, customers are willing to accept any variation of the product complying with their customization rules. The problem of constructing the final assembly production plan in such a setting is addressed by matching the available machines and other manufacturing resources to meet the demands with flexible customization. A branch-price-cut method to solve this problem without using auxiliary binary variables is developed and computational examples of the implementation of the method are presented. [ABSTRACT FROM AUTHOR]