Flexible workshop scheduling optimization method and system considering crane transportation process

A technology for workshop scheduling and transportation process, applied in control/adjustment system, general control system, program control, etc., to achieve the effect of reducing the maximum completion time and total energy consumption, and improving the efficiency of processing and transportation

Pending Publication Date: 2021-01-29
SHANDONG NORMAL UNIV
View PDF3 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies in the prior art, the object of the present invention is to provide a flexible workshop scheduling optimization method and system considering the crane transport

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Flexible workshop scheduling optimization method and system considering crane transportation process
  • Flexible workshop scheduling optimization method and system considering crane transportation process
  • Flexible workshop scheduling optimization method and system considering crane transportation process

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0052]Example one:

[0053]This embodiment provides a flexible workshop scheduling optimization method considering the crane transportation process, such asfigure 1 Shown, including:

[0054]Obtain the parameters of the flexible workshop, the parameters including the number of machines in the target factory, the number of workpieces, the processing procedures corresponding to each workpiece, the processing machines corresponding to each procedure, the processing time of the workpiece, and the position coordinates of the crane;

[0055]Based on the parameters of the flexible workshop, a flexible workshop scheduling model is constructed; the flexible workshop scheduling model aims to minimize the maximum completion time and total energy consumption;

[0056]Based on a hybrid algorithm of distribution estimation and variable neighborhood search, the flexible shop scheduling model is solved, and the flexible shop scheduling plan is output after the solution. Among the output solutions of the flexib...

Example Embodiment

[0194]Embodiment two:

[0195]In this embodiment, the hybrid algorithm described in the first embodiment is subjected to experimental analysis to evaluate its performance. The algorithm and other comparison algorithms are implemented in C++ and run on an Intel Core i7 2.6-GHz 8GB memory computer. Comparison algorithms include Girish and PSO algorithms, VNS algorithm, GA algorithm and IG algorithm.

[0196]In order to compare the performance of the algorithm with other algorithms, the following relative percentage increase (RPI) performance indicators are proposed:

[0197]

[0198]Where fcIs the average fitness value of a given algorithm, fbIs f in all comparison algorithmscThe optimal value.

[0199]This embodiment includes four types of calculation examples. The first type of calculation example is a small-scale calculation example, where the number of workpieces is I={7,9,10}, and the number of machines is M=6. The second type of calculation examples are medium-scale calculation examples, a tot...

Example Embodiment

[0231]Embodiment three:

[0232]This embodiment provides a flexible workshop scheduling optimization system considering the crane transportation process, including:

[0233]The parameter acquisition module is configured to acquire the parameters of the flexible workshop, the parameters including the number of machines in the target factory, the number of workpieces, the processing procedures corresponding to each workpiece, the processing machines corresponding to each procedure, the processing time of the workpiece, and the crane Location coordinates;

[0234]The flexible workshop scheduling model building module is configured to: build a flexible workshop scheduling model based on the parameters of the flexible workshop; the flexible workshop scheduling model aims at the maximum completion time and the minimization of total energy consumption;

[0235]The scheduling plan output module is configured to solve the flexible shop scheduling model based on a hybrid algorithm of distribution estimat...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a flexible workshop scheduling optimization method and system considering a crane transportation process. The method comprises the following steps: obtaining the parameters ofa flexible workshop, wherein the parameters comprise the number of machines in the target factory, the number of workpieces, the machining process corresponding to each workpiece, the machining machine corresponding to each process, the machining time of the workpieces and the position coordinates of the crane; constructing a flexible workshop scheduling model based on the parameters of the flexible workshop, wherein the flexible workshop scheduling model aims at minimizing the maximum completion time and the total energy consumption; and solving the flexible workshop scheduling model based ona mixed algorithm of distribution estimation and variable neighborhood search, and outputting a flexible workshop scheduling scheme after solving, wherein all individual solutions in the output solutions of the flexible workshop scheduling model are arranged according to the increasing sequence of fitness values. According to the invention, a hybrid algorithm of distribution estimation and variable neighborhood search is provided to solve the flexible workshop scheduling problem, so that the factory production efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of production scheduling, in particular to a flexible workshop scheduling optimization method and system considering the crane transportation process. Background technique [0002] The flexible job-shop scheduling problem (FJSP) is an extension of the classic job-shop scheduling problem. FJSP allows each process to be processed by one of many machines that can be processed. FJSP is used to solve manufacturing problems, involving chemical material manufacturing, equipment manufacturing, mobile phone assembly, semiconductor manufacturing, etc. In FJSP, techniques for solving single-objective FJSP and multi-objective FJSP have gradually been developed. For the single-objective FJSP algorithm, makespan is often used as the optimization objective. For multi-objective FJSP, optimization objectives include makespan, delay, energy consumption, processing load, etc., which are more abundant than single-objective FJ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32252Y02P90/02
Inventor 杜宇李俊青
Owner SHANDONG NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap