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Flexible factory work scheduling method based on MapReduce parallelization in cloud computing environment

A cloud computing environment, job scheduling technology, applied in computing, comprehensive factory control, comprehensive factory control, etc.

Active Publication Date: 2016-05-04
SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional algorithm implementation is based on the consideration of a single-node computing environment. At present, there are almost no relevant methods to consider the algorithm implementation under the distributed computing model in the cloud computing environment.

Method used

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  • Flexible factory work scheduling method based on MapReduce parallelization in cloud computing environment
  • Flexible factory work scheduling method based on MapReduce parallelization in cloud computing environment
  • Flexible factory work scheduling method based on MapReduce parallelization in cloud computing environment

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Embodiment 1

[0045] Embodiment 1: a flexible factory job scheduling method based on MapReduce parallelization in a cloud computing environment according to the present invention. MapReduce is a programming model for parallel computing of large-scale data sets (greater than 1 TB). Using the elastic computing method of cloud computing environment, FJSP is realized as a cloud service. Users can submit computing tasks remotely and put forward requirements on time and precision. After the cloud accepts the tasks, it allocates computing resources according to the scale and requirements of the tasks, and uses MapReduce to perform parallel calculations on FJSP, and finally feeds back the result Gantt chart to users . Compared with the traditional single-node computing method, the present invention can meet the time and accuracy requirements of users.

[0046] This method mainly includes two parts of work:

[0047] The first step, the establishment of the cloud computing environment: receive the ...

Embodiment 2

[0080] Embodiment 2: a flexible factory job scheduling method based on MapReduce parallelization under a cloud computing environment according to the present invention, the processing schedule of the flexible job shop scheduling problem is shown in Table 1:

[0081] Table 1 Processing schedule for the flexible job shop scheduling problem

[0082]

[0083] Step 1. Randomly generate initial solution individuals according to the flexible job shop scheduling problem, and form an initial population

[0084] FJSP must not only determine the processing sequence of the process, but also choose a suitable machine for each process, so the coding is divided into two parts:

[0085] (1) Coding based on the process (determining the processing sequence of the process)

[0086] Through the distributed execution of multiple mappers, multiple process sets are first generated, and then a reducer is used to deduplicate the process sets to obtain an initial process set as follows:

[0087] ...

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Abstract

The invention discloses a flexible factory work scheduling method based on MapReduce parallelization in a cloud computing environment. The method comprises the following steps of: receiving a remotely submitted flexible work shop scheduling problem, allocating computing resource according to a computing task and task requirements through a cloud computing elastic mode, wherein the flexible work shop scheduling problem comprises the computing task, and the task requirements of computing time and computing precision for the computing task; according to the computing resource allocated in the first step, modeling for the flexible work shop scheduling problem submitted by a user and coding the computing task, then, solving with a MapReduce parallelization genetic algorithm, and finally providing a scheduling result. In the method provided by the invention, a MapReduce model is used, thus, requirements of the user on time and precision can be satisfied, algorithm solving time can be reduced effectively, and solution quality can be improved.

Description

technical field [0001] The invention relates to a method for solving flexible factory operation problems, in particular to a method for scheduling flexible factory operations based on MapReduce parallelization in a cloud computing environment. Background technique [0002] Production scheduling optimization is the core technology of advanced manufacturing technology and modern management technology. Many scholars at home and abroad have conducted research, but most of the research is on the optimization of the classic job scheduling problem JSP (Job-ShopSchedulingProblem). In classic JSP, the sequence of processes for each workpiece is predetermined, and each process is processed on a designated machine. In actual production, the process is allowed to be processed on any one of multiple machines. This kind of problem is the flexible job shop scheduling problem. FJSP (FlexibleJob-ShopSchedulingProblem) reduces machine constraints, expands the search range of feasible solution...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G05B19/418
CPCG05B19/41865G05B2219/39167G06Q10/06313Y02P90/02
Inventor 王江晴帖军毛腾跃孙翀雷建云周斌
Owner SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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