Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Hybrid genetic algorithm for solving multi-objective flexible job-shop scheduling problem

A hybrid genetic algorithm, flexible operation technology, applied in control/regulation systems, instruments, comprehensive factory control, etc., can solve the problems of difficult decoding, time-consuming calculation, complex coding methods, etc., to enhance the search ability, simplify the coding process, The effect of avoiding computation time

Inactive Publication Date: 2017-05-03
SICHUAN YONGLIAN INFORMATION TECH CO LTD
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Even though many algorithms have been proposed, they all have complex encoding methods, which makes decoding difficult and consumes a lot of computing time

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
  • Hybrid genetic algorithm for solving multi-objective flexible job-shop scheduling problem
  • Hybrid genetic algorithm for solving multi-objective flexible job-shop scheduling problem
  • Hybrid genetic algorithm for solving multi-objective flexible job-shop scheduling problem

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention and not to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0032] The invention aims at the problem that some current algorithms do not consider multi-objective flexible job shop scheduling, and the genetic algorithm in the prior art has the problems of global near-optimality and difficult decoding process. The invention proposes a hybrid genetic algorithm to solve the multi-objective flexible job shop scheduling problem. Among them, time, cost and equipment uti...

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 provides a hybrid genetic algorithm for solving a multi-objective flexible job-shop scheduling problem. The algorithm takes three objectives of the completion time, the production cost and the equipment utilization rate in flexible job-shop scheduling into consideration, and aims at the circumstances that algorithms at present are difficult in decoding and long in computation time because of possession of a complicated coding method and that the genetic algorithm is faced with problems of global near optimum and insufficient search capability in local search. In allusion to the problems, the invention provides a new matrix chromosome coding method which almost does not need to perform decoding. In addition, the algorithm provided by the invention combines the global search capability and local search of the genetic algorithm, the search capability of the algorithm is enhanced, and a feasible solution is found more easily. The hybrid algorithm is high in practicability, and can be well applied to flexible job-shop scheduling.

Description

[0001] Technical field [0002] The invention relates to the technical field of job shop scheduling, in particular to the field of multi-objective flexible job shop scheduling. Background technique [0003] The Flexible Job Shop Scheduling Problem (FJSP) is a scheduling in which machines and processes have multiple choices. Typically, it includes machine allocation and process scheduling. The method for job shop scheduling problem is the key method to improve the work efficiency, flexibility and reliability of production. It is of great practical significance to deeply study the problem of flexible job shop scheduling and propose an efficient algorithm, especially for enterprises in a fierce competition environment. [0004] Compared with the traditional job shop scheduling problem, the flexible job shop scheduling problem has fewer constraints, so the search space for feasible solutions is larger. Therefore, it is more difficult and is an NP-hard problem. Existing algorit...

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): G05B19/418
CPCG05B19/41865G05B2219/32252
Inventor 汤琴胡成华
Owner SICHUAN YONGLIAN INFORMATION TECH CO LTD
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
Eureka Blog
Learn More
PatSnap group products