Research on Precise Determination of Dynamic Target Indicators and Optimal Resource Allocation Strategies Based on Binary Search and Genetic Algorithms

Abstract

This study addresses the challenges of precisely determining dynamic target indicators and optimizing single-resource allocation strategies. For effective coverage of cylindrical targets by resources within a specific airspace, we first establish the kinematic equations governing the motion of missiles, resource carriers, and deployed resources. To accurately calculate effective engagement duration, we construct a cylindrical occlusion indicator function, which determines occlusion status based on the minimum distance between the line-of-sight and the center of the resource cloud. To enhance computational accuracy and overcome limitations of traditional time-scanning methods, this study innovatively employs a binary search algorithm to precisely locate discontinuity points where the occlusion indicator function value jumps, thereby accurately calculating the effective duration of resource-target occlusion. Building upon this foundation, a nonlinear single-objective optimization model was developed. This model uses the UAV's heading angle, velocity, deployment time, and fuse delay as decision variables, with the objective of maximizing the total effective coverage duration. The optimization model was solved using a genetic algorithm simulating biological evolution, yielding optimal resource deployment parameter combinations that significantly enhance resource allocation performance.