基于多目标粒子群优化的无人机协同多任务分配

doi:10.3969/j.issn.1006-2475.2016.08.002

计算机与现代化

基于多目标粒子群优化的无人机协同多任务分配

(1.海军航空工程学院控制工程系，山东烟台 264001; 2.江西外语外贸职业学院，江西南昌 330099;
3.中国人民解放军91331部队修理厂，辽宁葫芦岛 125106)

收稿日期:2016-02-22 出版日期:2016-08-18 发布日期:2016-08-11
作者简介:尹高扬(1987-)，男，湖南湘潭人，海军航空工程学院控制工程系讲师，博士，研究方向：导航制导与控制; 周绍磊(1963-)，男，教授，博士，研究方向：导航制导与控制; 莫骏超(1990-)，男，江西吉安人，江西外语外贸职业学院讲师，本科，研究方向：自动化; 曹明川(1988-)，男，辽宁人，中国人民解放军91331部队修理厂助理工程师，硕士，研究方向：固体火箭发动机使用工程; 康宇航(1989-)，男，江西吉安人，博士研究生，研究方向：导航制导与控制。
基金资助:
航空科学基金资助项目(20135184007)

Multiple Task Assignment for Cooperating Unmanned Aerial Vehicles Using Multi-objective Particle Swarm Optimization

(1. Department of Control Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China;
2. Jiangxi College of Foreign Studies, Nanchang 330099, China; 3. Repair Shop, Unit 91331 of PLA, Huludao 125106, China)

Received:2016-02-22 Online:2016-08-18 Published:2016-08-11

摘要/Abstract

摘要： 将多无人机协同多任务分配问题描述为一个多目标优化问题。采用基于Pareto占优的多目标离散粒子群算法（MODPSO）对该问题进行求解。通过矩阵编码方式建立粒子与实际问题的映射，满足协同多任务分配的时序约束和多机协同约束。设计符合实际问题特点的粒子群位置和速度更新策略。仿真结果验证了所提模型和算法的有效性。

关键词: 多任务分配, 多目标, 无人机, 离散粒子群

Abstract: The problem of assigning multiple tasks on multiple targets for a group of cooperating unmanned aerial vehicles (UAVs) is discribed as a multi-objective optimization problem. An approach in which Pareto dominance is incorporated into discrete particle swarm optimization (DPSO) in order to allow this heuristic to handle the problem is proposed. The structure of particle’s position vector space in the algorithm enforces the required task precedence and coordination a new update strategy for the position and speed of particle is applied. Simulation results demonstrate the effectiveness and feasibility of the proposed model and approach.,

Key words: multiple task assignment, multi-objective, UAV, discrete particle swarm

中图分类号:

V249.122

尹高扬1，周绍磊1，莫骏超2，曹明川3，康宇航1. 基于多目标粒子群优化的无人机协同多任务分配[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2016.08.002.

YIN Gao-yang1, ZHOU Shao-lei1, MO Jun-chao2, CAO Ming-chuan3, KANG Yu-hang1. Multiple Task Assignment for Cooperating Unmanned Aerial Vehicles Using Multi-objective Particle Swarm Optimization[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.08.002.

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基于多目标粒子群优化的无人机协同多任务分配

Multiple Task Assignment for Cooperating Unmanned Aerial Vehicles Using Multi-objective Particle Swarm Optimization

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