An ensemble optimisation approach to service composition in cloud manufacturing

A Novel Service Composition Algorithm for Cloud-Based Manufacturing Environment

“…For a single task, the corresponding manufacturing resources will be directly executed, but for a complex and large-scale task, the CMP will decompose it into several subtasks and allocate them to corresponding manufacturing resources. Hence, the users can use all kinds of dynamic application services in an ondemand way with the support of the CMfg operation platform and realize the multi-agent collaborative interaction [16]. The platform makes providers increase the conversion rate from design to production and demanders increase the utilization rate of manufacturing resources at the same time, so this is a win-win platform.…”

“…Que et al [15] proposed an improved adaptive immune genetic algorithm for optimal QoS-aware service composition selection in cloud manufacturing. In order to select the best combination of services to perform a customer's requests, Fazeli et al [16] adopted an ensemble optimization approach to cope with such a problem. Zhou and Yao [4] and Zhou et al [5] gave two countermeasures respectively to handle the many-objective CMSC problems.…”

Service Composition and Optimal Selection in Cloud Manufacturing: State-of-the-Art and Research Challenges

“…Hybrid GA Matlab Rnd C C Max [62] CNBA N/A Rnd C N-C N-C [16] Fuzzy Set N/A N/A C C Max [7] Empirical Knowledge GA C# Collect C C Max [63] GA N/A Rnd C C Max [17] Branch-And-Cut Gams Rnd C C Max [64] GSA [66] Bat Algorithm N/A Rnd C C Min [67] Hybrid ICA Matlab Rnd C C Min [68] BBO C# Real C C Max [69] Hybrid PSO (PSO_SA) Matlab Rnd C N-C N-C [70] SSO Ensemble Python Rnd C C N-C [71] Graph-based N/A SG C C Max [72] GA N/A Rnd C C Max [14] IHDETBO Matlab Rnd C C Max [73] Improved SFLA Visual Studio Rnd C C Max [74] Hybrid GWO Matlab SG C C Max [75] GA Matlab Rnd C C Max [76] Improved GA based on entropy Matlab Rnd C C Max [77] Improved GWO Matlab Rnd C C Max [78] GA…”

“…Case study [52] Magnetic bearing assembly [20] Manufacturing of magnetic bearing [22] Molding industry [61] Customized automobile parts [62] Alloy materials processing to customize car doors and painting [25] High-performance mechanical seals provider in challenging work conditions [57] Large-scale verification of proposed algorithm with artificial bee colony and cuckoo search strategies to identify the correlation impact [58] Performance of proposed case study based on searching ability and composite service dynamic trust QoS [60] Composite CMfg service optimal selection (CCSOS) on large-scale (Customized motorcycle production) [67] Service-oriented collaborative manufacturing system support 10 SMEs for the motorcycle production industry [64] Numerical case study based on original data from CMfg service scheduling simulation experiment [23] Simulated data set to evaluate algorithms for service composition and optimal selection problems of various scales [68] Variable candidate, arrival times and weight combinations [4] Cloud environment for the customized car design and production [71] Numerical example considering available services, and service performance similarity [70] Parameters setup with random seed for repeatable results [75] MC type wheeled cleaning robot manufacturing [14] Consists of the raw material life cycle based on representative components from two hundred thousand bill of materials (BOM) data [72] Molding industry cloud manufacturing prototype [78] Numerical case study for large scale problem on CMfg logistic service sharing requirements [81] Demand-driven system simulation to satisfy users' needs considering the real-world service provider capacity restrictions [80] Mold manufacturing service composition containing the entire life cycle from mold design to testing and packing. in service composition and optimal selection in the field of CMfg has received increasing attention since 2013, so it is essential to identify the studies with promising solutions to relay a foundation for future research.…”

Research on Diffusion Mechanism of Green Innovation of Cloud Manufacturing Enterprises Based on BA Scale-Free Agglomeration Network Game

“…After integrating cloud computing, the Internet of things and other emerging technologies [5], the "cloud manufacturing" mode can seamlessly connect the information and resources of manufacturing enterprises and allow manufacturing resources to be easily shared under cloud services, which can promote the development of the manufacturing industry to become more agile, service-oriented, green and intelligent [8]. Cloud manufacturing enterprises can build virtual enterprise alliances through cloud manufacturing platforms to share green technology or manufacturing resources to improve the speed of technological innovation and enterprise performance [9], [10], which has accelerated the realization of "agile manufacturing", "service-oriented manufacturing", "green manufacturing" and "created in China" [6], [7]. Therefore, it is particularly important to accelerate the implementation of the green technology innovation of cloud manufacturing enterprises.…”