Cloud manufacturing service combination optimization method based on improved genetic algorithm

A technology for improving genetic algorithm and service composition, applied in the field of cloud manufacturing service composition optimization based on improved genetic algorithm, can solve problems such as seldom considering the influence of non-functional service quality parameters, and achieve the goal of overcoming inconsistent metric standards, meeting complex needs, The effect of suppressing precocious puberty

Active Publication Date: 2021-05-14
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

They studied service composition modeling and optimization algorithms to solve the optimization problem of functional service quality parameters ...

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  • Cloud manufacturing service combination optimization method based on improved genetic algorithm
  • Cloud manufacturing service combination optimization method based on improved genetic algorithm
  • Cloud manufacturing service combination optimization method based on improved genetic algorithm

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Embodiment Construction

[0042] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings.

[0043] The invention provides a cloud manufacturing service combination optimization method based on an improved genetic algorithm. According to user requests, on the basis of the QoS evaluation model of cloud manufacturing service combination, the combination Objective functions such as synergy degree and combination entropy, establish a mathematical model for cloud manufacturing service combination optimization, apply improved genetic algorithm to search, and provide a multi-objective optimization solution for cloud manufacturing service combination optimization problems, such as figure 1 As shown, it specifically includes the following steps:

[0044] Step 1: According to the user's request, based on the QoS evaluation model of the cloud manufacturing service portfolio, the multi-objective cloud manufacturing service portfoli...

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Abstract

The invention discloses a cloud manufacturing service combination optimization method based on an improved genetic algorithm. The method comprises the steps: synthesizing the execution time and execution cost of a task according to a user request on the basis of a QoS evaluation model of a cloud manufacturing service combination, combining the objective functions, such as a service configuration degree, a combination collaboration degree, a combination entropy, and the like, establishing a mathematical model for cloud manufacturing service combinatorial optimization, using an improved genetic algorithm for searching, and providing a multi-objective optimization solution for the cloud manufacturing service combinatorial optimization problem. By means of the method, the initial population can keep good stability, in the early stage of the algorithm, the two-point crossover operation is adopted to expand the search space, and the population gene diversity is improved. In the later stage of the algorithm, single-point crossover operation is adopted, convergence is accelerated, search time is shortened, and therefore the problem of falling into local optimum is better avoided.

Description

technical field [0001] The invention belongs to the field of cloud manufacturing services, and in particular relates to a combination optimization method for cloud manufacturing services based on an improved genetic algorithm. Background technique [0002] Cloud manufacturing is a new service-oriented manufacturing model. Through the virtualization and serviceization of various manufacturing resources and manufacturing capabilities, it provides users with various manufacturing resources, which can be accessed at any time and stored in the cloud. Payment for services. In order to meet the complex manufacturing needs of customers, fine-grained simple cloud services can be combined into coarse-grained complex cloud services through service composition. Complex cloud services are executed in a distributed, heterogeneous and autonomous environment to complete highly uncertain and dynamic manufacturing tasks. Choosing the best combination of cloud services to successfully execut...

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Application Information

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IPC IPC(8): G06Q10/04G06F17/16G06N3/00G06N3/12
CPCG06Q10/04G06F17/16G06N3/006G06N3/126
Inventor 周井泉陈怡
Owner NANJING UNIV OF POSTS & TELECOMM
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