Three-dimensional box loading method based on three-dimensional moving mode sequence and memetic algorithm

A pattern sequence, three-dimensional movement technology, applied in genetic modeling, computing, data processing applications, etc., can solve the problem of low volume utilization, achieve the effect of large volume utilization, speed up convergence, and reduce storage capacity

Active Publication Date: 2015-04-08
XIDIAN UNIV
View PDF4 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that it is only suitable for weakly heterogeneous three-dimensional

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
  • Three-dimensional box loading method based on three-dimensional moving mode sequence and memetic algorithm
  • Three-dimensional box loading method based on three-dimensional moving mode sequence and memetic algorithm
  • Three-dimensional box loading method based on three-dimensional moving mode sequence and memetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0029] The three-dimensional box packing problem of the present invention refers to packing as many boxes as possible into a fixed container under the condition of satisfying a feasible placement scheme, so as to maximize the volume utilization rate of the container, and to test the data.

[0030] An important feature of the present invention is to expand the two-dimensional mobile pattern sequence to three-dimensional, and use the method of projecting the box to the plane to record the attribute value of the box, and its design model is:

[0031] Let Edgxz indicate that the box is projected onto the xoz plane, Edgxy indicate that the box is projected onto the xoy plane, and Edgyz indicate that the box is projected onto the yoz plane.

[0032] Information from Edgxz includes:

[0033] xl: When the box is projected onto the xoz plane, the minimum x-coordinate value of the boundary;

[0034] xr: When the box is projected onto the xoz plane, the maximum x coordinate value of the...

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 three-dimensional box loading method based on a three-dimensional moving mode sequence and a memetic algorithm. The method mainly solves the problem of low utilization rate on the volume of a three-dimensional box loading container in the prior art. The three-dimensional box loading method comprises the following realization steps that 1, each parameter is set; 2, an initial population is randomly generated, and the adaptive fitness of individuals in the population is calculated; 3, whether the termination conditions are met or not is judged, if so, the step 4 is executed, and otherwise, the step 9 is executed; 4, a binary tournament method is used for selecting the individuals; 5, the individuals are crossed, and the individual adaptive fitness value is calculated again; 6, the individuals are subjected to variation, and the individual adaptive fitness value is calculated again; 7, the individual with the greatest adaptive fitness value in the current generation is stored; 8, the number of the iteration times is added to 1, and the operation returns to the step 3; 9, a hill climbing method is used for optimizing the individuals with the greatest adaptive fitness value, and the optimized box loading result is output. The method has the advantages that the volume utilization rate of the container can be improved, and the method can be used for solving the box loading problem, and can also be used for soling other combination optimization problems.

Description

technical field [0001] The invention belongs to the technical field of computer optimization, and further relates to a three-dimensional box packing method, which can be used to optimize the coordinates of box placement and realize the optimization of box packing in logistics and other industries. Background technique [0002] Three-dimensional packing 3D-BPP is a problem often encountered in industrial production, such as ship container loading and unloading, aircraft freight management, warehouse management, etc. In the process of cargo loading and transportation, efficient utilization of resources and transportation space is the core competitiveness among companies. Therefore, due to its practical needs, seeking a reasonable and effective placement strategy is still an important direction of research. [0003] "A hybrid genetic algorithm for packing in 3D with deepest bottom left with fill method" ("Advances in Information Systems", article number: 441-450 (2004)) publis...

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): G06Q10/04G06N3/12
CPCG06N3/12G06Q10/04
Inventor 刘静焦李成韩二丽朱园马文萍马晶晶
Owner XIDIAN 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