基于优先排序与粒子群优化的装备保障任务规划方法

针对装备保障任务规划过程中保障资源占用冲突及保障任务逻辑关系约束的实际问题，构建基于任务优先排序的解空间模型，并进一步提出基于优先排序与改进粒子群优化的装备保障任务规划方法。该方法将分解后的保障任务按照其重要性和逻辑顺序进行优先排序，并根据排序结果对粒子群优化算法得到的任务与资源匹配解空间进行调整，以解决资源占用冲突和逻辑顺序问题。为保证每次迭代后的粒子为可行解，提出不可行粒子的多维异步处理机制，提高了粒子群优化算法的搜索效率。通过实例应用仿真分析，验证了该方法在装备保障任务规划中的有效性和优越性。

A Planning Method of Equipment Support Task Based on Priority Ordering and Particle Swarm Optimization Algorithm

A solution space model based on task priority ordering is constructed according to the practical problem of support resource occupancy conflicts and logical relationship among support tasks in the process of equipment support task planning. A planning method of equipment support task based on priority ordering and improved particle swarm optimization is further proposed. In the proposed method, the decomposed support tasks are ordered by priority according to their importance and logical order. According to the sorted results, the task and the resource matching solution space obtained by the particle swarm optimization algorithm are adjusted for solving the problem of resource occupancy and logical sequence. A multi-dimensional asynchronous processing mechanism is proposed to ensure that the particles are feasible, so that the search efficiency of the particle swarm optimization algorithm is improved. The effectiveness and advantage of the method in the planning of equipment support tasks are verified by examples and contrastive simulation analysis. The method has broad application prospects in the field of equipment support assistant decision-making technology.