An Optimal Allocation Method for Virtual Resource Considering Variable Metrics of Cloud Manufacturing Service

2015 ◽  
Author(s):  
Jin Cui ◽  
Lei Ren ◽  
Lin Zhang ◽  
Qiong Wu
Keyword(s):  
High Efficiency ◽  
Optimal Allocation ◽  
Pso Algorithm ◽  
Agile Manufacturing ◽  
Cloud Manufacturing ◽  
Virtual Manufacturing ◽  
Allocation Problem ◽  
Allocation Model ◽  
Manufacturing Resources ◽  
Optimization Allocation

Based on the concept of Cloud Computing, a new service-oriented, high efficiency low consumption, knowledge-based, and intelligent networked agile manufacturing model Cloud Manufacturing (CMfg) has been proposed recently. The manufacturing resources optimization allocation model (MROAM) is one of the core parts for implementing CMfg. In this paper, a new MROAM is proposed in the background of CMfg system. In this model, variable metrics such as a variety of evaluation indicators for different types of manufacturing services are taken into account. In addition, time, cost, virtual manufacturing resource interface, and so on constrains are considered as well. To solve the manufacturing resources optimization allocation problem, a new improved intelligent algorithm named Kmeans-PSO was presented by combining the particle swarm optimization (PSO) algorithm and the K-means clustering. Experiment results demonstrate the effectiveness of the designed algorithm and show Kmeans-PSO’s high performances for addressing the manufacturing resources allocation problem compared with other intelligent algorithms.

Study on the Multi-Granularity Virtualization of Manufacturing Resources

2013 ◽  
Author(s):  
Chunsheng Hu ◽  
Chengdong Xu ◽  
Xiaobo Cao ◽  
Pengfei Zhang
Keyword(s):  
Large Scale ◽  
Cloud Manufacturing ◽  
Virtual Manufacturing ◽  
Networked Manufacturing ◽  
Manufacturing Resources ◽  
Manufacturing Mode

As a new kind of networked manufacturing mode, Cloud Manufacturing needs to construct a large-scale virtual manufacturing resources pool firstly. For a reasonable and effective construction of the virtual manufacturing resources pool, the point of multi-granularity virtualization is proposed. Firstly, by analyzing the process of resources virtualization, the meanings of manufacturing resources, virtualization modeling and virtualization accessing are stated, and the relationships between them are illustrated; secondly, by analyzing the compositionality of resources, two resources categories are deduced; thirdly, the granularity factor, which have serious impacts on the resources-virtualization, resources-matching and resources-scheduling, are discussed; finally, a multi-granularity virtualization method of manufacturing resources is proposed.

A Resource Optimization Allocation Strategy for China’s Shipbuilding Industry Green Innovation System

2020 ◽  
Vol 17 (04) ◽  
pp. 2050029
Author(s):  
Kexin Bi ◽  
Kwangil An ◽  
Xiang Li
Keyword(s):  
Innovation System ◽  
Pso Algorithm ◽  
Resource Optimization ◽  
Allocation Strategy ◽  
Green Innovation ◽  
Allocation Model ◽  
Shipbuilding Industry ◽  
Proposed Model ◽  
Resource Data ◽  
Optimization Allocation

In order to realize the resource optimization allocation in the green innovation system of China’s shipbuilding industry under the internet environment, to improve the level of green innovation and to reduce the resource consumption, a resource optimization allocation model and the corresponding allocation strategy are proposed. The model integrates and shares the innovation resource data through Internet of Things (IOT) technology, and optimizes the allocation decision by using the cooperative differential game and Particle Swarm Optimization (PSO) algorithm. At the same time, it ensures the robustness of green innovation system and realizes the optimization allocation of resources. A case study is given to illustrate the feasibility of the model. The results show that the green innovation subject can carry out strategic interaction by adjusting the allocation proportion of innovation resources through the proposed model, so as to optimize the overall green innovation benefits of the system.

Computational Trust in Cloud Manufacturing

2013 ◽  
Vol 774-776 ◽  
pp. 1908-1913 ◽  
Author(s):  
Lu Gao ◽  
Quan Liu ◽  
Ping Lou
Keyword(s):  
Manufacturing Systems ◽  
Service Providers ◽  
Cloud Manufacturing ◽  
Trust Model ◽  
Virtual Manufacturing ◽  
Manufacturing Environment ◽  
Collaborative Relationships ◽  
Computational Trust ◽  
Service Oriented ◽  
Manufacturing Resources

Cloud manufacturing is a new kind of advanced service-oriented network manufacturing paradigm. There are two kinds of nodes in this network manufacturing environment: manufacturing service nodes (service providers) encapsulated by manufacturing resources and task nodes (service customers). One of the bases of building up the collaborative relationships between customers and providers in cloud manufacturing environment is their reciprocal trust. However, vicious, mendacious, and inveracious information makes it quite difficult for customers to find reliable and high-quality providers to form virtual manufacturing systems for efficiently responding to market demands in cloud manufacturing environment, viz. service consumers often have insufficient information on service providers. The trustworthy network manufacturing environment is a prerequisite to implementation of cloud manufacturing. In this paper the notion of human trust is extended to the cloud manufacturing. A computational trust model which combines the direct computational reliability and the computational reputation is presented, and the simulating result confirms it valid.

Research on Mass Manufacturing Resource Sensory Data Management Based on Hadoop

2016 ◽  
Vol 693 ◽  
pp. 1880-1885 ◽  
Author(s):  
Kai Kai Su ◽  
Wen Sheng Xu ◽  
Jian Yong Li
Keyword(s):  
Distributed Storage ◽  
Cloud Manufacturing ◽  
Distributed File System ◽  
Service Platform ◽  
Sensory Data ◽  
Computing Model ◽  
Hadoop Distributed File System ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Management Method

Aiming at the management issue of mass sensory data from the manufacturing resources in cloud manufacturing, a management method for mass sensory data based on Hadoop is proposed. Firstly, characteristics of sensory data in cloud manufacturing are analyzed, meanings and advantages of Internet of Things and cloud computing are elaborated. Then the structure of the cloud manufacturing service platform is proposed based on Hadoop, the information model of manufacturing resources in cloud manufacturing is defined, and the data cloud in the cloud manufacturing service platform is designed. The distributed storage of mass sensory data is implemented and a universal distributed computing model of mass sensory data is established based on the characteristics of Hadoop Distributed File System (HDFS).

Mathematical Models for Predicting and Managing Water Resources — The Case of China in 2025

2013 ◽  
Vol 448-453 ◽  
pp. 995-1001
Author(s):  
Ning Na Wang ◽  
Qin Lin Zhou
Keyword(s):  
Water Supply ◽  
Water Demand ◽  
Optimal Allocation ◽  
Supply And Demand ◽  
Decision Makers ◽  
Grey System ◽  
Allocation Model ◽  
Water Supply Management ◽  
Generate Solution ◽  
Major Factors

An effective management of water supply is critically significant to a countrys water utilities, and accurate prediction of water supply and demand is of key importance for water supply management. The objectives of this paper are to use Grey System Model (GSM) and Linear Regression Model to forecast the water demand and water supply respectively in China 2025, and then propose a new Optimal Allocation Model (OAM) to generate solution so that analysts and decision makers can gain insight and understanding. The two predictive models take into account four major factors including domestic development, agriculture, industries and eco-environment, calculating a deficit between water demand and water supply in China 2025. Then the OAM, which considers desalinization, irrigation saving and urban recycling, provides a feasible solution to fill the gap and an effectual management of water supply.

Cloud Manufacturing Resource Management Based on Metadata

2015 ◽  
Author(s):  
Chun Zhao ◽  
Lin Zhang ◽  
Xuesong Zhang ◽  
Liang Zhang
Keyword(s):  
Resource Management ◽  
Cloud Manufacturing ◽  
State Monitoring ◽  
Knowledge Resources ◽  
Centralized Management ◽  
Service Oriented ◽  
Manufacturing Resources ◽  
Resource Data ◽  
Manufacturing Platform ◽  
Management Approaches

Centralized management and sharing of manufacturing resources is one of the important functions of cloud manufacturing platform. There are many kinds of manufacturing resources, centralized management, optimized scheduling, quick searching for various manufacturing resources become important issues in a cloud manufacturing platform. This paper presents a resource management model based on metadata to realize the access and unified management of the hardware resources, software resources and knowledge resources. Two management approaches respectively for static and dynamic resource data are introduced to realize resource state monitoring and real-time information collecting. On this basis, the relationship between static and dynamic data is determined and service-oriented of resources is realized.

scholarly journals Modeling and Resolution of the Allocation Problem of the Time Slots in Dakar Airport

2017 ◽  
Vol 9 (3) ◽  
pp. 30
Author(s):  
Youssouf Ahamada ◽  
Salimata G. Diagne ◽  
Amadou Coulibaly ◽  
D'ethi'e Dione ◽  
N'dogotar Nlio ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Linear Model ◽  
Optimal Allocation ◽  
Allocation Problem ◽  
Quality Service ◽  
Unmet Demand ◽  
Proposed Model ◽  
Optimal Quality ◽  
Leopold Sedar Senghor

In this article, we proposed a programming linear model in integer numbers(PLIN) for the optimal allocation of the time slots in the  international  Leopold Sedar Senghor airport of Dakar (L.S.S). The slots  are specific allocated periods which allow an aircraft to land or take off in a saturated airport. Their attribution depends on theconfiguration of the airport, more particularly on its capacity. We maximize the confirmed demand in each slot and take the number of aircrafts and the number of manageable passengers with an optimal quality service into account. We used the CPLEX software so that to test the effectiveness of the linear model. Firstly, in the proposed model linear in integer numbers, any unmet demand was isolated. Secondly, the rejected demands  by introducing a model and an algorithm of resolution based on the dynamic programming.

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