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Combination optimizing method facing bin packing problem

A bin packing problem and combinatorial optimization technology, applied in the fields of instruments, data processing applications, prediction, etc., can solve problems such as difficult to find the global optimal solution, weak genetic search effect, high redundancy of coding methods, etc., to improve the design Efficiency, solve the effect of fast packing, optimize the design

Inactive Publication Date: 2008-12-10
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

[0003] In terms of computational complexity, the bin packing problem is an NP problem, and it is difficult to find an accurate global optimal solution.
The encoding methods of these two methods have the disadvantage of high redundancy, and more importantly, they both ignore the structure of the combinatorial problem, so the effect of genetic search will be weakened

Method used

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  • Combination optimizing method facing bin packing problem
  • Combination optimizing method facing bin packing problem
  • Combination optimizing method facing bin packing problem

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Embodiment

[0027] The combinatorial optimization method for bin packing problem includes the following steps:

[0028] 1) Consider a one-dimensional box packing problem with 8 items, the size of the box is a random number between (0, 1), and the size of the box is 1. A box can contain one item or multiple items, but the total size of the items contained cannot exceed the size of the box. The solution of the bin-packing problem is encoded using the chromosome coding method of the combinatorial genetic algorithm. The chromosome coding of the combinatorial genetic algorithm is divided into an item part and a group part. For a one-dimensional bin packing problem with 8 items, the items are numbered from 0 to 7, respectively.

[0029] 01234567,

[0030] Then a chromosome of the bin packing problem can be written as

[0031] ADBCEBAB:ADBCE,

[0032] Indicates that items 0 and 6 are packed in a box named A, 1 is packed in D, 2, 5, and 7 are packed in B, 3 is in C, and 4 is in E. The item par...

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Abstract

The invention discloses a combined optimization method for problems related to containers. Aiming at the problems relating to the combined optimization and operation deployment in industrial production, the invention adopts a coding form that takes group as object and is suitable for the problematic combination structure, so that a genetic algorithm can pass information that is related to the problems about chromosome heredity. The invention classifies the chromosome into an object part and a group part to generate chromosomes with different length. Besides, the invention, by utilizing a mutation operator and an inverse operator designed according to the characteristics of combination problem, carries out the iteration of algorithm for a plurality of times and finally acquires the quasi-optimal combined solution to the problem. Therefore, aiming at the problem of the container that an accurate global solution is hard to get, the invention adopts the combined optimized method by taking groups as objects, which effectively realizes the optimized design of container problems, resolves the design for fast stuffing and enhances the design efficiency.

Description

technical field [0001] The invention relates to the field of solving combinatorial optimization problems, in particular to a combinatorial optimization method oriented to bin packing problems. Background technique [0002] Packing problems widely exist in industrial production, such as fabric cutting in the garment industry, container loading in the transportation industry, plate-type blanking in the processing industry, layout in the printing industry, and packaging and sorting objects in real life. It is also widely used in computer science, such as multiprocessor task scheduling, resource allocation, file allocation, memory management and other low-level operations are all practical applications of bin packing problems. [0003] In terms of computational complexity, the bin packing problem is an NP problem, and it is difficult to find an accurate global optimal solution. Approximate algorithms for solving such problems include heuristic algorithms and search algorithms. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12G06Q10/00G06Q50/00G06Q10/04G06Q50/28
Inventor 罗仕鉴卜满钊张劲松应放天杨颖
Owner ZHEJIANG UNIV
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