Cloud manufacturing scheduling method based on Grover quantum search algorithm

Abstract

The invention relates to a cloud manufacturing scheduling method based on a Grover quantum search algorithm. The cloud manufacturing scheduling method includes the steps: initializing quantum registerstates, setting a cost consumption function and a tensor product; taking a state register as an initial value; and taking M state registers from the N states by using an improved quantum Grover search algorithm, and carrying out minimum search, wherein if the cost consumption function of any new state register is smaller than the initial cost consumption function, the current state register is ascheduling optimal solution, and the scheduling state matrix corresponding to the current state register is taken as an optimal scheduling matrix, otherwise, the optimal scheduling matrix is taken asan initial scheduling state matrix, and an optimal scheduling matrix is output. According to the cloud manufacturing scheduling method, the task allocation planning speed in the cloud manufacturing scheduling problem is increased, and the quantum Grover algorithm is used for conducting hierarchical screening firstly, and most of non-optimal scheduling solutions can be filtered out to change the situation that a plurality of solutions need to be traversed originally into the situation that only a few solutions need to be traversed, and therefore the original problem is simplified, and the search speed is increased.

Description

technical field [0001] The present invention relates to the technical field of program control devices, for example, controllers, in particular to a cloud manufacturing scheduling method based on Grover's quantum search algorithm. Background technique [0002] During the operation of the cloud manufacturing platform, service providers and demanders continuously submit their own manufacturing requirements to the cloud manufacturing platform, and the cloud manufacturing platform provides users with optimal manufacturing services based on the individual needs of each user and generates a scheduling plan for tasks and services ; The matching and scheduling process of manufacturing tasks and manufacturing services is the core of solving the supply-demand matching and effective resource utilization of the cloud manufacturing platform. This process needs to consider the optimal selection of different manufacturing services. [0003] In the existing technology, there are still few s...

AI Technical Summary

Problems solved by technology

[0004] The present invention solves the problem of scheduling tasks and services of manufacturing resources in the cloud manufacturing environment in the prior art. There are still few studies, and the methods used are mainly intelligent optimization algorithms, and there are some game theory methods. These methods are often iterative Complicated, the task allocation and planning speed in the cloud manufacturing scheduling process is slow, and it cannot cope with the increasingly large manufacturing tasks and manufacturing service matching and scheduling requirements of the cloud manufacturing platform. An optimized cloud based on Grover's quantum search algorithm is provided. Manufacturing Scheduling Method