Task allocation method based on heuristic dynamic deepening optimization algorithm

Abstract

The invention provides a task allocation method based on a heuristic dynamic deepening optimization algorithm, and the method comprises the building of a task allocation model and the solving of the task allocation model, and comprises the steps: S1, building the task allocation model based on intention deviation degree, command complexity, confrontation threat degree and combat risk degree; S2, solving a task allocation model, including the steps: S2.1, carrying out solution space construction and initialization; S2.2, creating a node to be expanded. Compared with the prior art, the task allocation method based on the heuristic dynamic deepening optimization algorithm is applied to solve the task allocation problem that multiple troops use multiple weapons to strike multiple targets; comprehensive quantitative evaluation of superior intention realization degree, command control complexity degree, survival threat resistance degree and operational risk degree can be realized, rapid solving of the model is realized through mixed optimization strategies such as reward value inspiration, iteration deepening and dynamic memory, and a task allocation scheme can be rapidly and effectively given.

Description

technical field [0001] The invention relates to the technical field of resource allocation, in particular to a task allocation method based on a heuristic dynamic deepening optimization algorithm. Background technique [0002] Task allocation is a key link for command organizations at all levels to carry out operational command and decision-making activities. It is mainly based on the constraints of available resources, and the process of specifying the battlefield to be used, the target points, and the types and quantities of weapons to be launched. Task allocation must meet multiple constraints such as weapon performance, available resources, and battlefield environment, and achieve multiple desired goals such as realizing the superior's intention, facilitating the operational command of the troops, and reducing the confrontation threat and operational risk faced by the weapon attack process. Obviously, this problem is a typical multi-constraint multi-objective nonlinear N...

AI Technical Summary

Problems solved by technology

Obviously, this problem is a typical multi-constraint multi-objective nonlinear NP optimization problem

Since the backtracking method is essentially a deep search algorithm, its computational time complexity is the power-square relationship of the problem solution space, which makes it impossible to guarantee a satisfactory solution within a limited time

Therefore, the search algorithm can not meet the requirements of the use

[0004] With the rapid development of new technologies and weapons and the increase in the complexity of modern battlefields, the scale of weapon types and the number of targets that can be attacked have led to an exponential increase in the scale of task assignment problems, and modeling and solving are extremely difficult. For multi-force use There is no effective and quick solution to the task allocation problem of multiple weapons striking multiple targets

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