Adaptive genetic algorithm-based mixed flow shop sustainable scheduling control method

A genetic algorithm and continuous scheduling technology, applied in the field of sustainable scheduling control of mixed flow workshops, can solve problems such as shortages, and achieve the effect of improving automation level, improving efficiency, and simple algorithm process

Active Publication Date: 2019-05-17
TONGJI UNIV
View PDF9 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, there is still a lack of research on the hybrid flow shop scheduling technology with t

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
  • Adaptive genetic algorithm-based mixed flow shop sustainable scheduling control method
  • Adaptive genetic algorithm-based mixed flow shop sustainable scheduling control method
  • Adaptive genetic algorithm-based mixed flow shop sustainable scheduling control method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0045] Such as figure 1As shown, the present invention provides a hybrid flow shop sustainable scheduling control method based on an adaptive genetic algorithm, by establishing the sustainability goals and constraints of the mixed flow shop scheduling of the final process batch processing, and using an adaptive genetic algorithm to solve Scheduling model is optimized scheduling scheme to control workpiece machining process.

[0046] The method specifically includes the following steps:

[0047] Step 1), obtain workshop processing information, including the number of workpieces, proc...

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 relates to an adaptive genetic algorithm-based mixed flow shop sustainable scheduling control method. The method comprises the following steps of: 1) obtaining shop processing information which comprises a workpiece number, processing procedures, a machine number on each procedure, processing time of the workpieces on the machines, unit residence energy consumption of the workpieces,unit waiting energy consumption of the machines and last procedure batch processing information; 2) establishing a mixed flow shop scheduling model, taking minimized energy consumption as a target, for last procedure batch processing; and 3) solving the scheduling model by adoption of an adaptive genetic algorithm so as to obtain an optimized scheduling scheme. In the adaptive genetic algorithm,encoding and genetic recombination are carried out in a layering manner on the basis of mixed flow shop processing characteristics, and populations are updated by adoption of adaptive crossing and mutation probabilities. Compared with the prior art, the method has the advantages of being obvious in energy saving effect and high in solving efficiency.

Description

technical field [0001] The invention relates to the technical field of production energy-saving control in the manufacturing industry, in particular to a sustainable scheduling control method for a mixed flow shop based on an adaptive genetic algorithm. Background technique [0002] Although there have been many research results on the Hybrid Flowshop Scheduling (HFS) problem, most of the research has simplified the actual problem and lacked the consideration of the complex scheduling situation in the actual production environment. It is reflected in that, on the one hand, current research results often aim at optimizing production performance, for example, minimizing the maximum completion time, total processing time, and total delay time. However, with the emergence of environmental issues and rising energy costs, more and more attention has been paid to the sustainable development of manufacturing, especially how to optimize energy consumption in the production process is...

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): G05B19/418G06F17/18G06N3/12G06Q10/06G06Q50/04
CPCY02P90/30
Inventor 乔非卢弘
Owner TONGJI 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