scholarly journals A modified discrete invasive weed algorithm for optimal service composition in cloud manufacturing systems

2018 ◽  
Vol 17 ◽  
pp. 403-410 ◽  
Author(s):  
Hamed Bouzary ◽  
F. Frank Chen ◽  
Krishnan Krishnaiyer
Keyword(s):  
Service Composition ◽  
Manufacturing Systems ◽  
Cloud Manufacturing ◽  
Invasive Weed ◽  
Optimal Service

scholarly journals Blockchain-based cloud manufacturing platforms: A novel idea for service composition in XaaS paradigm

2021 ◽  
Vol 7 ◽  
pp. e743
Author(s):  
Seyyed-Alireza Radmanesh ◽  
Alireza Haji ◽  
Omid Fatahi Valilai
Keyword(s):  
Service Composition ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Manufacturing System ◽  
Service Oriented Architecture ◽  
Time Synchronization ◽  
Main Idea ◽  
Cloud Manufacturing ◽  
Blockchain Technology ◽  
Service Oriented

Cloud manufacturing is a new globalized manufacturing framework which has improved the performance of manufacturing systems. The service-oriented architecture as the main idea behind this framework means that all resources and capabilities are considered as services. The agents interact by way of service exchanging, which has been a part of service composition research topics. Service allocations to demanders in a cloud manufacturing system have a dynamic behavior. However, the current research studies on cloud-based service composition are mainly based on centralized global optimization models. Therefore, a distributed deployment and real-time synchronization platform, which enables the globalized collaboration in service composition, is required. This paper proposes a method of using blockchain to solve these issues. Each service composition is considered as a transaction in the blockchain concept. A block includes a set of service compositions and its validity is confirmed by a predefined consensus mechanism. In the suggested platform, the mining role in blockchain is interpreted as an endeavor for proposing the proper service composition in the manufacturing paradigm. The proposed platform has interesting capabilities as it can increase the response time using the blockchain technology and improve the overall optimality of supply-demand matching in cloud manufacturing. The efficiency of the proposed model was evaluated by investigating a service allocation problem in a cloud manufacturing system in four large scale problems. Each problem is examined in four centralized modes, two, three and four solvers in blockchain-based model. The simulation results indicate the high quality of the proposed solution. The proposed solution will lead to at least 15.14% and a maximum of 34.8 percent reduction in costs and 20 to 68.4 percent at the solving time of the problem. It is also observed that with increasing the number of solvers (especially in problems with larger dimensions) the solution speed increases sharply (more than 68% improvement in some problems), which indicates the positive effect of distribution on reducing the problem-solving time.

scholarly journals A Heuristic Algorithm for Optimal Service Composition in Complex Manufacturing Networks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Yinan Wu ◽  
Gongzhuang Peng ◽  
Hongwei Wang ◽  
Heming Zhang
Keyword(s):  
Service Composition ◽  
Optimal Path ◽  
Cloud Manufacturing ◽  
Search Procedure ◽  
Manufacturing Networks ◽  
Composition Problem ◽  
Optimal Service ◽  
Manufacturing Platform ◽  
Manufacturing Network ◽  
Composition Path

Service composition in a Cloud Manufacturing environment involves the adaptive and optimal assembly of manufacturing services to achieve quick responses to varied manufacturing needs. It is challenged by the inherent heterogeneity and complexity of these services in terms of their diverse and complex functions, qualities of service, execution paths, etc. In this paper, a manufacturing network is constructed to explicitly identify and describe the relationships between individual services based on their attributes. On this basis, the service composition problem can be modeled as a multiple-constrained optimal path (MCOP) selection problem by taking into account different types of composition, namely, sequence, parallel, selection, and cycle. A novel Dual Heuristic Functions based Optimal Service Composition Path algorithm (DHA_OSCP) is proposed to solve the NP-Complete MCOP problem, which involves exploiting the backward search procedure with different search targets to obtain two heuristic functions for the forward search procedure. The proposed algorithm is evaluated through a set of computational experiments in which the proposed algorithm and other popular algorithms such as MFPB_HOSTP are applied to the same dataset, and the results obtained show that DHA_OSCP can efficiently find the optimal service composition path with better Quality of Service (QoS). The viability of DHA_OSCP is further proved in a case study of services composition on a Cloud Manufacturing platform.

scholarly journals Modelling of cross organizational manufacturing resource service chain based on service supply-demand dynamic matching network

2019 ◽  
Vol 277 ◽  
pp. 01005
Author(s):  
Qingqing Yang ◽  
Jia Liu ◽  
Kewei Yang
Keyword(s):  
Network Theory ◽  
Service Composition ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Matching Network ◽  
Dynamic Matching ◽  
Composition Problem ◽  
Resource Service

In the cloud manufacturing systems, both manufacturing tasks and manufacturing services are in a dynamic environment. How could cloud manufacturing platform optimizes manufacturing cloud services based on QoS, matching an optimal service composition for manufacturing tasks has become an urgent problem at present. In view of this problem, we study the matching of manufacturing tasks and manufacturing services from the perspective of complex network theory. On the basis of manufacturing task network and manufacturing service network, a dynamic matching network theory model of manufacturing task-service is constructed. And then, we take a dynamic assessment of QoS. Finally, we use load and dynamic QoS as the optimization objectivities, transform the optimal manufacturing service composition problem into the shortest path problem, and the dynamic scheduling of manufacturing services is realized.

Interoperability in Cloud Manufacturing and Practice on Private Cloud Structure for SMEs

2017 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Security Requirements ◽  
Research Trend ◽  
Safety Regulations ◽  
Multiple Challenges ◽  
New Research

In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

scholarly journals Dynamic Pricing in Cloud Manufacturing Systems under Combined Effects of Consumer Structure, Negotiation, and Demand

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Peng ◽  
Wei Guo ◽  
Lei Wang ◽  
Ruo-Yu Liang
Keyword(s):  
Dynamic Pricing ◽  
Manufacturing Systems ◽  
Wholesale Price ◽  
Cloud Manufacturing ◽  
High Ratio ◽  
Reservation Price ◽  
Combined Effects ◽  
Constant Elasticity ◽  
Price Increases ◽  
Linear Demand

In this study, we proposed a game-theory based framework to model the dynamic pricing process in the cloud manufacturing (CMfg) system. We considered a service provider (SP), a broker agent (BA), and a dynamic service demander (SD) population that is composed of price takers and bargainers in this study. The pricing processes under linear demand and constant elasticity demand were modeled, respectively. The combined effects of SD population structure, negotiation, and demand forms on the SP’s and the BA’s equilibrium prices and expected revenues were examined. We found that the SP’s optimal wholesale price, the BA’s optimal reservation price, and posted price all increase with the proportion of price takers under linear demand but decrease with it under constant elasticity demand. We also found that the BA’s optimal reservation price increases with bargainers’ power no matter under what kind of demand. Through analyzing the participants’ revenues, we showed that a dynamic SD population with a high ratio of price takers would benefit the SP and the BA.

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