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Simulation modeling and analysis with Arena
Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.\" It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. · Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems· Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling* Ample end-of-chapter problems and full Solutions Manual* Includes CD with sample ARENA modeling programs
eBook
A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives
With the rapid advancement of cyber-physical systems, Digital Twin (DT) is gaining ever-increasing attention owing to its great capabilities to realize Industry 4.0. Enterprises from different fields are taking advantage of its ability to simulate real-time working conditions and perform intelligent decision-making, where a cost-effective solution can be readily delivered to meet individual stakeholder demands. As a hot topic, many approaches have been designed and implemented to date. However, most approaches today lack a comprehensive review to examine DT benefits by considering both engineering product lifecycle management and business innovation as a whole. To fill this gap, this work conducts a state-of-the art survey of DT by selecting 123 representative items together with 22 supplementary works to address those two perspectives, while considering technical aspects as a fundamental. The systematic review further identifies eight future perspectives for DT, including modular DT, modeling consistency and accuracy, incorporation of Big Data analytics in DT models, DT simulation improvements, VR integration into DT, expansion of DT domains, efficient mapping of cyber-physical data and cloud/edge computing integration. This work sets out to be a guide to the status of DT development and application in today’s academic and industrial environment.
Journal Article
The orchestrating role of platform enterprises in digital inclusion: A network game perspective from industrial clusters
The digital transformation of industrial clusters, while enhancing productivity, has exacerbated the corporate digital divide, particularly for small and medium-sized enterprises (SMEs). Digital inclusion, which aims to bridge this divide, exhibits public-good attributes and positive externalities, yet its co-construction is often hindered by the “Olson’s dilemma” arising from the conflict between individual and collective rationality. Platform enterprises, occupying the “bridging point” of structural holes within clusters, are posited to act as opinion leaders capable of orchestrating ecosystem co-creation. Through a theoretical simulation approach, there employs a “small-world + opinion leader” complex network framework to model the evolutionary dynamics of digital inclusion ecosystem co-construction. Integrating a public goods game model with a Fermi learning algorithm enhanced by a random surfer mechanism, we simulate strategic interactions among cluster firms under controlled parameter conditions. Monte Carlo simulations reveal a distinct threshold effect under simulated conditions: cooperation emerges sustainably only when the investment return coefficient surpasses the critical value defined by the number of game participants. Furthermore, the platform’s connection ratio and strategic commitment emerge as pivotal factors; maintaining an investment strategy significantly promotes cooperation, whereas free-riding by the platform exerts a strong negative demonstration effect. While traditional platform governance tools like rewards and punishments can mitigate cooperation decay, they cannot reverse collective free-riding trends in our model. Crucially, a binding collective agreement, featuring pre-commitment of costs and redistribution of unused funds, emerges as the most effective mechanism for resolving the cooperation dilemma within the simulation. These theoretically derived findings offer insights for policymakers, platform enterprises, and SMEs in fostering collaborative and inclusive digital ecosystems within industrial clusters, though empirical validation remains necessary.
Journal Article
Cyber security threat modeling based on the MITRE Enterprise ATT&CK Matrix
Enterprise systems are growing in complexity, and the adoption of cloud and mobile services has greatly increased the attack surface. To proactively address these security issues in enterprise systems, this paper proposes a threat modeling language for enterprise security based on the MITRE Enterprise ATT&CK Matrix. It is designed using the Meta Attack Language framework and focuses on describing system assets, attack steps, defenses, and asset associations. The attack steps in the language represent adversary techniques as listed and described by MITRE. This entity-relationship model describes enterprise IT systems as a whole; by using available tools, the proposed language enables attack simulations on its system model instances. These simulations can be used to investigate security settings and architectural changes that might be implemented to secure the system more effectively. Our proposed language is tested with a number of unit and integration tests. This is visualized in the paper with two real cyber attacks modeled and simulated.
Journal Article
Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality
Using a combination of theoretical discussion and real-world case studies, this book focuses on current and future use of RAISA technologies in the tourism economy, including examples from the hotel, restaurant, travel agency, museum, and events industries.
eBook
Digital Twin Framework for Large-Scale Optimization Problems in Supply Chains: A Case of Packing Problem
The development of new information technologies at the beginning of the 21st century allows the integration between the physical and the virtual world. In Engineering, an emerging technology called digital twins is presented as the mechanism to virtualize the operation of devices, machines and processes. In industrial engineering and specifically in supply chains there is a growing interest in the development of digital twins. For this reason, this paper proposes the integration of large-scale optimization problems in a digital platform that allows the solution of these problems for decision-making in real time. Bin-Packing and Vehicle Routing problems are addressed through the interface of a commercial supply chain management platform and heuristic optimization algorithms. We use technology based on simulation of discrete events to achieve the periodic decisions that make up the Digital Supply ChainTwin engine. A hypothetical case solution is presented to verify the performance of the proposed development.
Journal Article
A blockchain-based secure storage and access control scheme for supply chain finance
Supply chain finance (SCF) provides credit for small and medium-sized enterprises with low credit lines and small financing scales. The resulting financial credit data and related business transaction data are highly confidential and private. However, traditional SCF management schemes use third-party platforms and centralized designs that cannot achieve highly reliable secure storage and fine-grained access control. To address such a need, we propose Fabric-SCF, designing and implementing a Blockchain-based secure storage system by utilizing distributed consensus to realize data security, traceability, and immutability. The attribute-based access control model is deployed for access control, also utilizing smart contracts to define system processes and access policies to ensure the system’s efficient operation. To verify the performance of Fabric-SCF, two sets of simulation experiments are designed its effectiveness. Experimental results show that Fabric-SCF achieves dynamic and fine-grained access control while maintaining high throughput in a simulated real-world operating scenario.
Journal Article