Adaptive coefficient genetic algorithm-based cloud manufacturing service resource matching method

A technology of adaptive coefficients and service resources, which is applied in the field of cloud manufacturing service resource matching based on adaptive coefficient genetic algorithms, can solve problems such as inability to correspond one-to-one, and achieve the effects of improving accuracy, increasing diversity, and fast convergence speed

Active Publication Date: 2018-02-09
GUILIN UNIV OF ELECTRONIC TECH
View PDF6 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Cloud manufacturing service resources can complete a certain number of manufacturing and processing procedures, but the user's processing and manufacturing tasks include a se...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Adaptive coefficient genetic algorithm-based cloud manufacturing service resource matching method
  • Adaptive coefficient genetic algorithm-based cloud manufacturing service resource matching method
  • Adaptive coefficient genetic algorithm-based cloud manufacturing service resource matching method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific examples and with reference to the accompanying drawings.

[0043] The cloud manufacturing service resource matching method based on the adaptive coefficient genetic algorithm of the present invention solves the best service resource combination to provide processing services for the user's manufacturing tasks. First define the description model of service resources and manufacturing tasks; define the minimum sum of the product of all task costs and time as the objective function; set the parameters of the genetic algorithm and initialize the population; then calculate the value of the objective function of each individual in the population and judge the capacity Limit, discard individuals that do not meet the capacity requirements, calculate the adaptive coefficient and then calculat...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention discloses an adaptive coefficient genetic algorithm-based cloud manufacturing service resource matching method. According to the method, the value of the objective function of each individual in a population is calculated, and the capacity limit of each individual is judged; individuals which do not meet capacity requirements are discarded; an adaptive coefficient is calculated; the selection probability, crossover probability and mutation probability of iteration of a current round are calculated; genetic evolution is carried out according to the probabilities, so that anew population can be generated; and the population is supplemented with new individuals. According to the method of the invention, an optimal resource service combination matched with the task requirement of a cloud manufacturing user is solved according to the task requirement of the cloud manufacturing user; it can be ensured that the sum of the products of the cost and time of all tasks is minimum; the capacity limitation of resource services is satisfied, so that queuing and waiting can be avoided; and since an improved genetic algorithm has high robustness and fast convergence rate andwill not be trapped in local optimum, the diversity of the population can be significantly improved, and the accuracy of resource matching can be improved.

Description

technical field [0001] The invention relates to the technical field of cloud manufacturing, in particular to a method for matching cloud manufacturing service resources based on an adaptive coefficient genetic algorithm. Background technique [0002] Network manufacturing models such as traditional manufacturing grids and agile manufacturing have technical and model bottlenecks and cannot be promoted on a large scale. For this reason, combined with existing advanced manufacturing models and technologies and new technologies such as cloud computing, Internet of Things, virtualization, and service-oriented technology, the concept of cloud manufacturing was born. [0003] Cloud manufacturing adopts the cutting-edge concept of contemporary information technology (especially cloud computing), and expands the concept of "software as a service" to "manufacturing as a service", which will become an important model of my country's Industry 4.0. Due to the diversity, complexity, and ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q10/06G06Q50/04H04L29/08G06N3/00G06N3/04
CPCH04L67/02G06N3/006G06Q10/06312G06Q10/06315G06Q50/04G06N3/047Y02P90/30
Inventor 张明李春泉尚玉玲李彩林党选举李晓冬
Owner GUILIN UNIV OF ELECTRONIC TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products