Data group optimization method and device, computer equipment and storage medium

An optimization method and technology of optimization algorithms, applied in the computer field, can solve problems such as difficult to find meta-heuristic algorithms

Inactive Publication Date: 2022-05-13
NAT UNIV OF DEFENSE TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When faced with a collection of diverse optimization problems, it is difficult to find a general metaheuristic algorithm to obtain a satisfactory solution

Method used

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  • Data group optimization method and device, computer equipment and storage medium
  • Data group optimization method and device, computer equipment and storage medium
  • Data group optimization method and device, computer equipment and storage medium

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Embodiment Construction

[0048] In order to make the purpose, technical solution and advantages of the present application clearer, the present application 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 application, and are not intended to limit the present application.

[0049]After years of development, there are already hundreds of optimization algorithms. For a specific optimization problem, especially when there is little information about the problem, it is impossible to judge which swarm intelligence optimization algorithm will be the best way to solve it. Although a better algorithm can be found through continuous trial and error, it is time-consuming and labor-intensive. In addition, for the solution of some problems, the search strategy of a single algorithm cannot find a satisfactory solution. For example, it is better to use the...

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Abstract

The invention relates to a data group optimization method and device, computer equipment and a storage medium. The method comprises the following steps: constructing an integrated algorithm library, when a to-be-optimized problem is optimized, respectively adopting optimization algorithms to virtually update a to-be-updated virtual population output by the last iteration to obtain a virtual population corresponding to each optimization algorithm of the current iteration, selecting an elite individual from the virtual population corresponding to each optimization algorithm, and performing optimization on the selected elite individual; the elite individuals form an elite group, the optimal elite individual is selected from the elite group, when the fitness value of the optimal elite individual is more than one order of magnitude smaller than the minimum fitness value in historical iteration, the virtual population where the optimal elite individual is located is materialized, and an entity population is obtained; and when the entity population meets a preset iteration output condition, outputting a population optimization result. By adopting the method, an optimization problem set containing different characteristics can be efficiently processed.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a data group optimization method, device, computer equipment and storage medium. Background technique [0002] Optimization tasks exist in many fields such as science, engineering, management, etc., and many optimization techniques have been proposed to accomplish these tasks. As one of the approximation methods, the meta-heuristic algorithm is not aimed at specific optimization problems, but is a general algorithm. [0003] Although a meta-heuristic algorithm can be applied to a variety of optimization problems, the solution obtained by it is not necessarily satisfactory for a specific optimization problem. According to the no-free-lunch theorem, there is theoretically no algorithm that is superior to other algorithms in solving all possible optimization problems. Therefore, in practice, researchers have designed a variety of meta-heuristic algorithms to solve vari...

Claims

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Application Information

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IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 李浩潘庆涛汤俊阮逸润詹建军秦婉亭万宇陈曦
Owner NAT UNIV OF DEFENSE TECH
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