Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

NSGA-II (non-domination sequencing genetic algorithm) multi-objective optimization searching method

A multi-objective optimization and search method technology, which is applied to the improvement field of the search method in the mainstream multi-objective optimization algorithm NSGA-II, can solve the problem of local convergence of the elite strategy, and prevent the search from converging in advance or falling into the local optimal solution, speeding up Search speed, the effect of increasing variety

Inactive Publication Date: 2012-12-19
JIANGSU UNIV
View PDF0 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the invention is to solve the local convergence problem brought by the elite strategy in the NSGA-II search method

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
  • NSGA-II (non-domination sequencing genetic algorithm) multi-objective optimization searching method
  • NSGA-II (non-domination sequencing genetic algorithm) multi-objective optimization searching method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0024] Such as figure 1 with figure 2 As shown, the NSGA-II multi-objective optimization search method includes the following steps:

[0025] (1) Randomly initialize the population as the first-generation parent population, with a size of N;

[0026] (2) Perform non-dominated sorting on the first-generation parent population, generate the first-generation sub-population after selection, crossover, and mutation, and then merge into a double population;

[0027] (3) Perform fast non-dominated sorting on the merged double population, first select the first-level non-dominated individual set N 1 , randomly drop D i Individuals are filled into the parent population of the next generation; among them, the number of individuals discarded at each level D 1 、D 2 ...D i ...D n It is proportional to the ratio of the number of non-dominated individual sets at this level to the population number, that is

[0028] D. 1 =N 1 *(N 1 / N),D 2 =N 2 *(N 2 / N),……D i =N i *(N i / N)...

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 an NSGA-II (non-domination sequencing genetic algorithm) multi-objective optimization searching method which comprises the following steps: randomly initializing a population as a first generation of father population, wherein the number of the population is N; carrying out non-domination sequencing on the first generation of father population, generating a first generation of child population after selection, intersection and heteromorphosis, and combining into a twice population; carrying out rapid non-domination sequencing on the combined twice population, firstly selecting a first stage non-domination individual set N1 and filling into a next generation of father population after abandoning D1 individuals randomly, and selecting a next stage non-domination individual set Ni (i=2, 3,..., n) in sequence and filling into a next generation of father population till the last stage of non-domination individual set Nn after abandoning Di individuals randomly, wherein the last stage is the set that the non-domination individual set is larger than a rest filling space of the next generation of father population; carrying out the congestion degree calculation on the last stage of non-domination individual set Nn after abandoning Dn individuals randomly; filling individuals with larger congestion distances into the rest space of the next generation of father population; carrying out genetic operation such as selection, intersection and heteromorphosis on the next generation of father population so as to generate the next generation of child population; and combining the next generation of child population and turning to the step (3).

Description

technical field [0001] The invention belongs to the research field of multi-objective optimization search method, in particular to the improvement of the search method in mainstream multi-objective optimization algorithm NSGA-II. Background technique [0002] Genetic Algorithm (Genetic Algorithm) is a kind of randomized search method evolved from the evolution law of the biological world (survival of the fittest, genetic mechanism of survival of the fittest). It was first proposed by Professor J.Holland in the United States in 1975. Its main feature is to directly operate on structural objects, without restrictions on derivation and function continuity; it has inherent implicit parallelism and better global optimization capabilities. ; Using a probabilistic optimization method, it can automatically obtain and guide the optimized search space, and adjust the search direction adaptively, without definite rules. These properties of genetic algorithms have been widely used in f...

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): G06N3/12
Inventor 周莲英杨鹤标蒋玲朱捷健
Owner JIANGSU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com