New workpiece rescheduling optimization method based on adaptive genetic algorithm

A technology of genetic algorithm and optimization method, which is applied in the field of workpiece scheduling management in discrete manufacturing systems

Inactive Publication Date: 2019-07-26
BOHAI UNIV
View PDF3 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the current rescheduling methods of enterprises are based on the manual scheduling of dispatchers, but there is no scientific method to solve such important problems as the need to reschedule when new workpieces arrive in the workshop.

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
  • New workpiece rescheduling optimization method based on adaptive genetic algorithm
  • New workpiece rescheduling optimization method based on adaptive genetic algorithm
  • New workpiece rescheduling optimization method based on adaptive genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0072] The embodiment of the new workpiece rescheduling method provided by the present invention is as follows:

[0073] Step 1: Build a Mathematical Model

[0074] In a heat treatment station with a known initial workpiece set The initial schedule υ for a set of newly arrived jobs J N ={n O +1,...,n O +n N}, under the premise of meeting the actual process requirements, reschedule all the workpieces, so as to obtain the rescheduling scheme with the goal of minimizing the waiting time of all workpieces;

[0075] The mathematical model is described as follows:

[0076]

[0077] s.t.

[0078] w j (σ)≤K,j∈J O (2)

[0079] the s j (σ)≥r j ,j∈J (3)

[0080]

[0081] ros(σ)=ros(υ) (5)

[0082] Equation (1) is the objective function, that is, to minimize the sum of waiting times of all workpieces, w i Indicates the waiting time for workpiece i to be processed; in formula (2), the initial workpiece’s waiting time in rescheduling σ cannot exceed K; formula (3) ensure...

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 new workpiece rescheduling optimization method based on a self-adaptive genetic algorithm in a discrete manufacturing system containing a heat treatment process and taking energy conservation as a target. The new workpiece rescheduling optimization method comprises the following steps: establishing a mathematical model; performing initialization; determining initial values of the population size G, the crossover rate pc, the variation rate pm, the replacement rate pr, the upper limit t of the number of cycles and the number of local search times T; generating an initial population; whether rescheduling is optimal is judged, and if yes, the individual is the optimal rescheduling scheme; otherwise, executing sequential crossover, mutation operation and chromosome selection operation; finding a new rescheduling sequence which is superior to the current rescheduling solution through self-adaptive local area search; updating the population; stopping the criterion,if the total number of cycles reaches a specified upper limit value t, outputting an individual with a maximum right-worthiness function, and ending the calculation; otherwise, continuing to evolve the population. According to the method, three local area search operators of inversion, transfer and interchange are used for forming an adaptive local area search algorithm, and a better energy-savingrescheduling scheme can be obtained in a short time.

Description

technical field [0001] The invention belongs to the workpiece scheduling management technology of a discrete manufacturing system in the field of industrial engineering, and in particular relates to a workpiece rescheduling method based on an adaptive genetic algorithm for a discrete manufacturing system containing a heat treatment process with energy saving as the optimization goal. Background technique [0002] The key to the production management of modern manufacturing enterprises is to optimize resource allocation, and the production scheduling link is an important link to optimize enterprise resource allocation. The scale of my country's manufacturing industry has leapt to the first place in the world. The most important thing is to optimize resource allocation. Optimizing the production management of modern manufacturing enterprises is an important part of optimizing the resource allocation of enterprises. Therefore, how to obtain the optimal scheduling method to adap...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06N3/12
CPCG06Q10/06315G06N3/126
Inventor 郭艳东
Owner BOHAI 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