| With the improvement of the performance of the task execution platform and the level of informatization,it brings great challenges to the opposing parties,but also presents rare opportunities.Therefore,intelligent research on target assignment has become a hot issue in task planning.There are many factors involved in the target assignment problcm,including the number and location of platforms or targets,the performance of the platform,and the load required by the target,etc.Moreover,some of these factors,such as the number and location of platforms or targets,are variable,which makes target assignment problem become a typical non-deterministic polynomial complete problem.By using intelligent algorithm to solve the target assignment problem,the limiting factors can be considered more comprehensively,which makes the assignment scheme more reasonable.In addition,when the platform and target change dynamically,how to obtain a new assignment plan in a timely and efficient manner is a crucial issue for application scenarios where every second counts.Focusing on the target assignment model and ant colony algorithm,this paper studies the static and dynamic target assignment problems.The main contents are as follows.1.Combining the basic theory of target assignment problem—optimization method,and applying ant colony algorithm to target assignment problem,a static target assignment scheme is designed.Combined with the practical application of the project,a unified target assignment model is established for three assignment modes(one-to-one,one-to-multi,and multi-to-one).In the model,generate the ant colony according to the allocation mode firstly,and then carry out the optimization according to the rules of ant colony algorithm.According to the characteristics of the assignment mode,the constraint conditions are refined from the single platform performance and multi-platform coordination.In one-to-one and one-to-multi assignment modes,it focuses on the constraint of single platform performance.In multi-to-one assignment mode,it focuses on the constraint of collaboration between multiple platforms.According to the proposed static target assignment method,the three assignment modes are simulated,and the effect of constraint conditions are verified specifically.2.Aiming at the problem of sequential optimization of target access in one-to-multi assignment mode,this paper proposes an adaptive parameter algorithm for sequential optimization.This method enables the ant colony size and the number of iterations in the ant colony algorithm to adapt its value according to the number of targets.So as to be more suitable for the target order optimization part.A comparative simulation experiment was carried out with the method of fixed parameter values.The experimental results show that the parameter model in this paper can avoid the situation that too huge setting value causes too high time cost,and can also avoid the situation that the setting value is too low to obtain the optimal order.3.Aiming at the dynamic change of target and platform in the scene,according to the idea of multi-level target assignment,this paper studies and formulates the dynamic adjustment strategy of target assignment.By analyzing the key points,and the filter conditions and the constraints involved of four kinds of dynamic changes,the specific assignment scheme adjustment method of four kinds of changes is given.In this paper,the dynamic adjustment strategy is to adjust the assignment scheme in the dynamic change part,avoiding the global recalculation scheme.The experimental results prove that the dynamic adjutment strategy in this paper can realize the feasibility and accurate adjustment of the assignment plan. |
