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A Multi-platform Collaborative Dynamic Task Allocation Method under Uncertain Conditions

A technology of dynamic tasks and allocation methods, applied in design optimization/simulation, computer-aided design, etc., to achieve the effect of improving performance and low computational cost

Active Publication Date: 2020-09-25
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Heuristic algorithms have certain advantages in terms of solution time and effect, but there are few heuristic methods for complex dynamic collaborative task allocation problems, especially multi-objective problems.

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  • A Multi-platform Collaborative Dynamic Task Allocation Method under Uncertain Conditions
  • A Multi-platform Collaborative Dynamic Task Allocation Method under Uncertain Conditions
  • A Multi-platform Collaborative Dynamic Task Allocation Method under Uncertain Conditions

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Embodiment Construction

[0041] The present invention provides a multi-platform collaborative dynamic task allocation method under uncertain conditions, the basic idea is: the robust dynamic collaborative task allocation model proposed by the present invention models the coupling between the sensing platform and the weapon platform , and consider the dynamic adjustment process of allocation, making the model more realistic. The model also takes into account the uncertainty of the platform's combat effectiveness, and uses the Soyster robust model to effectively improve the worst-case performance under uncertain conditions. Unlike robust models based on scene analysis, this model is computationally cheap and only needs to evaluate the objective function once.

[0042] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0043] First, the present invention establishes a robust cooperative dynamic allocation model. This module includes two o...

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Abstract

The invention discloses a multi-platform collaborative dynamic task allocation method under uncertain conditions, comprising: generating an initial population containing P individuals, each individual being an allocation plan; an allocation plan consisting of multiple quaternions (s, i ,j,k) composition; the quaternion (s,i,j,k) indicates that the weapon platform i and the sensor platform j are assigned to the target k at the same time in the stage s; considering the coupling between the weapon platform and the sensor platform, and not Determine the combat effectiveness under the conditions, and design the overall cooperative combat effectiveness F 1 (t) and overall operational cost F 2 (t); to maximize F 1 (t) and minimize F 2 (t) is the objective function, and the genetic iteration of the population is carried out to obtain the final allocation plan. Using this scheme can obtain better allocation results with low computational cost.

Description

technical field [0001] The invention relates to the technical field of multi-platform collaboration, in particular to a dynamic task allocation method for weapon platform and sensor platform collaboration. Background technique [0002] In modern air defense operations, multi-platform collaborative task assignment is an urgent problem to be solved in the command and control system. It aims to manage the combat platforms interconnected through the network in a unified manner and assign tasks to them in order to achieve the optimal allocation of battlefield resources. , break through the "platform island" limitation of traditional platform-centric warfare, and ensure the efficient conduct of air defense operations. Combat platforms can be divided into two categories: sensor platforms and weapon platforms. [0003] Most of the existing models independently manage the sensing platform and the weapon platform, ignoring the interaction between them, but the two have a great coupli...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20
CPCG06F30/20
Inventor 陈晨胥文钦陈杰王春野
Owner BEIJING INSTITUTE OF TECHNOLOGYGY