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Cloud manufacturing service combination optimization method for large-scale multi-batch task cooperation

A service composition and optimization method technology, applied in the field of cloud manufacturing service composition optimization, can solve problems such as difficulty in obtaining optimal solutions, and achieve the effects of strong global optimization ability, fast convergence speed, and improved accuracy

Pending Publication Date: 2021-04-13
ZHEJIANG UNIV OF TECH
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

In MMSCE-CMSC, the traditional artificial bee colony algorithm (Artificial Bee Colony Algorithm, ABC) is difficult to obtain a stable optimal solution

Method used

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  • Cloud manufacturing service combination optimization method for large-scale multi-batch task cooperation
  • Cloud manufacturing service combination optimization method for large-scale multi-batch task cooperation
  • Cloud manufacturing service combination optimization method for large-scale multi-batch task cooperation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0033] Example: such as figure 1 As shown, a cloud manufacturing service combination optimization method for large-scale multi-batch task collaboration is as follows:

[0034] (1) Firstly, the manufacturing task Task(T) is divided into several subtasks, multiple candidate cloud services are selected on the cloud platform to form a candidate cloud service set, and a large-scale multi-batch task collaborative combination model oriented to cloud manufacturing service combination is established; The parameters in the model are set as follows:

[0035] (i) Manufacturing task: Task(T);

[0036] (ii) subtask set: SbT={sbt 1 ,sbt 2 ,...sbt i ,...,sbt n}, n is the number of subtasks; (iii) candidate cloud service set: RCSS i is the set of candidate cloud services corresponding to the i-th subtask, k i is the total number of corresponding cloud services;

[0037] (iv) Service combination plan: Indicates the number of combinations for executing the i-th subtask;

[0038] (...

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Abstract

The invention relates to a cloud manufacturing service combination optimization method for large-scale multi-batch task cooperation, and the method comprises the steps: optimizing an optimization process of a large-scale multi-batch task cooperation combination model based on a plurality of types of improved artificial bee colony algorithms; the cloud manufacturing service combination optimization problem oriented to large-scale multi-batch task cooperation being solved through the optimized large-scale multi-batch task cooperation combination model. The method has high robustness, the convergence speed is high, the global optimization capacity is high, and the solving accuracy is improved; and meanwhile, the production time is taken as an optimization target, the service combination optimization of large-scale multi-batch task cooperation in a cloud manufacturing environment is realized, and the whole task production time is shortened.

Description

technical field [0001] The invention relates to the technical field of group intelligence optimization, in particular to a cloud manufacturing service combination optimization method for large-scale multi-batch task collaboration. Background technique [0002] The cloud manufacturing system brings together a large number of manufacturing task requirements and service resources. The scale, dispersion, and heterogeneity of manufacturing tasks and resources lead to continuous changes in the application scenarios of cloud manufacturing service combinations. Compared with the traditional manufacturing task mode, the multi-batch collaborative manufacturing task mode has better performance in terms of shortening the production and processing cycle and facilitating operation and management. However, during the execution of large-batch tasks in cloud manufacturing, the total number of sub-batches that need to be transferred is huge, so the processing time is long. In order to effect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006Y02P90/30
Inventor 刘志李鹏航朱李楠沈国江
Owner ZHEJIANG UNIV OF TECH