A multi-task resource allocation method and system based on social genetic algorithm

By introducing social operator operations of social genetic algorithms in multi-task resource allocation, the problem of slow convergence of resource allocation algorithms in the existing technology is solved, fast and real-time resource allocation is achieved, and combat efficiency is improved.

CN118365065BActive Publication Date: 2025-03-28NAT UNIV OF DEFENSE TECH
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Patent Information

Application Number
CN202410529301.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-04-29
Publication Date
2025-03-28
Estimated Expiration
2044-04-29

AI Technical Summary

Technical Problem

In the case of limited combat resources in the existing technology, the convergence speed of multi-task resource allocation algorithm is slow, affecting the speed and real-time allocation of combat mission resource, and seriously affecting the utilization rate and efficiency of combat resources.

Method used

A multi-task resource allocation method based on social genetic algorithm is proposed. By introducing social operator operations, the local search ability of the genetic algorithm is enhanced, and the local optimality is quickly converged to local optimality through mutated operations, thereby improving resource allocation speed and real-time performance.

Benefits of technology

It significantly improves the convergence ability and speed of multi-task resource allocation, improves the real-time and resource utilization rate of combat mission resource allocation, and enhances combat efficiency.

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Abstract

The present invention provides a multi-task resource allocation method and system based on a social genetic algorithm, which relates to the technical field of resource scheduling; the method comprises: obtaining combat mission information and combat resource information, constructing a constrained optimization problem model; optimizing and solving the constructed constrained optimization problem model based on a social genetic algorithm solver, and taking the optimal individual of the population finally solved as the multi-task resource allocation result. The present invention can greatly improve the combat mission resource allocation speed and the real-time performance of combat missions, and improve resource utilization and combat efficiency in combat.
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