Decoupling of the Leading Order DGLAP Evolution Equation with Spin Dependent Structure Functions

Azadbakht, F. Teimoury; Boroun, G. R.

doi:10.1007/s10773-017-3581-6

Cited by 7 publications

(3 citation statements)

References 45 publications

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“…x [42]. C 2 , contains an optional service resource of C 2 x , and the corresponding optional service set is r 21 , r 22 , .…”

Section: Mathematical Model Of Node Matching and Evolutionary Solutionsmentioning

confidence: 99%

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment

Zhang

et al. 2021

Micromachines

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In order to reduce the cost of manufacturing and service for the Cloud 3D printing (C3DP) manufacturing grid, to solve the problem of resources optimization deployment for no-need preference under circumstance of cloud manufacturing, consider the interests of enterprises which need Cloud 3D printing resources and cloud platform operators, together with QoS and flexibility of both sides in the process of Cloud 3D printing resources configuration service, a task-service network node matching method based on Multi-Objective optimization model in dynamic hyper-network environment is built for resource allocation. This model represents interests of the above-mentioned two parties. In addition, the model examples are solved by modifying Mathematical algorithm of Node Matching and Evolutionary Solutions. Results prove that the model and the algorithm are feasible, effective and stable.

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“…x [42]. C 2 , contains an optional service resource of C 2 x , and the corresponding optional service set is r 21 , r 22 , .…”

Section: Mathematical Model Of Node Matching and Evolutionary Solutionsmentioning

confidence: 99%

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment

Zhang

et al. 2021

Micromachines

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“…where BMP-B is composed of different business logic modules according to cartoon image design and cartoon image modelling activities. The BMP-B logical relationship between two business logistics is concatenation and loop, and the constraint condition is that the two steps have a sequential relation [38]; BMP-C is composed of multiple sub-tasks, and the constraint condition is sequential and parallel.…”

Section: Case Studymentioning

confidence: 99%

Modeling of Cloud 3D Printing Service Hyper-Network in Service-Oriented Manufacturing Systems

2020

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According to the theory of a complex network, the overall characteristics are derived from complex interactions among its components, that is, network structure. For its service network, its overall characteristics are its functions. In view of the coordinated linkage between the 3D printing industry and the logistics industry, 3D printing is deeply integrated with Internet technology, digital casting technology and Internet + service platforms. We propose a hyper-network model of raw material suppliers, semi-finished product processors and finished product manufacturers that realize on-demand customization. To analyse, design, and build the cloud 3D printing manufacturing capability service competition network, we propose a 3D printing service node structure model based on a super network using a reference and cloud manufacturing service model. The model's mathematical structure is given in detail. Under this condition, it is necessary to discuss the interaction between the logistics service level, productivity level and product processing quantity. The process of the proposed model and method is given, and the validity is proven with a case study of a Cloud 3D printing service hyper-network in service-oriented manufacturing systems. INDEX TERMS Complex network, manufacturing resource services, service-oriented manufacturing (SOM), cloud manufacturing, cloud 3D printing, order-driven.

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“…In the C3DPOT network, the edges of each node are determined by the existence of a timing constraint relationship between MFG tasks. Similarly, the edges in the C3DPOT network represent the logical structure and dependencies between nodes (Azadbakht, et al 2018). In a real network, there is not only one edge between two nodes, which allows one node to be associated with several nodes and then indirectly connected to achieve information exchange between nodes.…”

Section: ) the Formation Of The Hypergraph Edgementioning

confidence: 99%

Architecture of Cloud 3D Printing Task Modeling for Nodes Dynamic Scheduling and Coupling Based on Complex Networks

Zhang

Liu

et al. 2020

IEEE Access

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To study the variation in resource allocation efficiency in a cloud 3D printing (C3DP) manufacturing grid, C3DP task modeling for a complex network model was established based on the dynamic coupling of nodes, taking cloud manufacturing resource characteristics such as distribution and diversity into account. Based on this idea, we propose an architecture of C3DP task modeling for complex networks based on the dynamic coupling of nodes. First, the model calculates the initial tasks and services by evaluating the quality of the manufacturing resources, and then, according to the strength of the correlations among various tasks and among services and tasks, a multiplex network model based on cloud tasks and services is constructed. Then, according to the description and its constraint structure definition of the C3DP order tasks, by using the intercept method for complex networks, this paper identifies the work breakdown structure of coupling task sets, simplifies the optimization process, and proposes a C3DP order task (C3DPOT) network modeling method. Third, on the basis of the formal description of C3DP service resources, an architecture of C3DP order task methods for complex networks based on the dynamic coupling of nodes is proposed. Finally, a Service_Net model example is designed to verify the feasibility of the method.

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Decoupling of the Leading Order DGLAP Evolution Equation with Spin Dependent Structure Functions

Cited by 7 publications

References 45 publications

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment

Modeling of Cloud 3D Printing Service Hyper-Network in Service-Oriented Manufacturing Systems

Architecture of Cloud 3D Printing Task Modeling for Nodes Dynamic Scheduling and Coupling Based on Complex Networks

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