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Distributed flow shop scheduling method and system with batch delivery constraint

A workshop scheduling and distributed technology, applied in the direction of control/adjustment system, general control system, instrument, etc., can solve problems with many parameters and complexity

Active Publication Date: 2021-01-29
SHANDONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In terms of algorithms, although many solutions to distributed flow workshops and even distributed flow workshop scheduling with batch delivery constraints have been proposed, such as particle swarm algorithm, these algorithms are easy to fall into local optimum, and there are many parameters, which are relatively complicated.

Method used

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  • Distributed flow shop scheduling method and system with batch delivery constraint
  • Distributed flow shop scheduling method and system with batch delivery constraint
  • Distributed flow shop scheduling method and system with batch delivery constraint

Examples

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Embodiment 1

[0053] This embodiment discloses a distributed flow shop scheduling method with batch delivery constraints. Regarding the distributed replacement flow shop and batch delivery problem (DFSP-BD), the DFSP-BD that combines DFSP and batch delivery to the customer process is an optimization question. DFSP-BD is used to solve the integration of production and distribution in DFSP, it has two steps: processing jobs in the processing stage, batch delivery of products. Specific steps such as figure 1 shown.

[0054] In the processing stage, first, a group of jobs J1, J2, J3..., Jn are randomly assigned to F factories F1, F2, F3..., Ff, and no changes are allowed after assignment. Then, in a distributed factory, jobs are processed on m identical machines, M1, M2, M3, ..., MM in the same order, and the processing time of the first machine in the factory is 0. In the end, a machine can only handle one job at a time. Each job must be processed on the previous machine and then processed...

Embodiment 2

[0149] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, the steps of the methods in the above-mentioned embodiments are realized. .

Embodiment 3

[0151] The purpose of this embodiment is to provide a computer-readable storage medium.

[0152] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the methods in the above implementation examples are executed.

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Abstract

The invention provides a distributed flow shop scheduling method and system with a batch delivery constraint. The method comprises the steps of taking the minimization of manufacturing time and totalenergy consumption as a target, enabling the manufacturing time to comprise the time of a processing stage and the time of a batch delivery stage, and enabling the total energy consumption to be the energy consumption of a truck transportation stage, solving the target to obtain a generated factory allocation vector, a generated job priority vector and a generated batch allocation vector, and performing distributed flow shop scheduling according to the vectors, and realizing minimization of the manufacturing time and the total energy consumption.

Description

technical field [0001] The disclosure belongs to the technical field of flow shop scheduling, and in particular relates to a distributed flow shop scheduling method and system with batch delivery constraints. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] With the rapid development of the manufacturing industry, many enterprises began to consider multiple factories working at the same time, forming distributed scheduling (DS). In DS, the Distributed Flow Shop Scheduling Problem (DFSP) is the most widely studied problem. To solve the DFSP problem, optimization objectives, constraints and algorithms are proposed. Hatami et al. proposed order-based setting time constraints to solve distributed problems. Ji et al. study the no-wait constraint when the processing and assembly times are random. Rifai and Nguyen solve the allocation problem...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32252
Inventor 李庆华李俊青
Owner SHANDONG NORMAL UNIV
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