新疆大学电气工程学院
纸质出版:2023
移动端阅览
[1]王喜敏,袁杰.基于混合算法的多机器人协作任务均衡规划研究[J].新疆大学学报(自然科学版)(中英文),2023,40(02):210-221.
[1]王喜敏,袁杰.基于混合算法的多机器人协作任务均衡规划研究[J].新疆大学学报(自然科学版)(中英文),2023,40(02):210-221. DOI: 10.13568/j.cnki.651094.651316.2022.04.25.0002.
DOI:10.13568/j.cnki.651094.651316.2022.04.25.0002.
针对机器人完成任务不均衡问题展开分析,提出了基于混合算法的规划算法,包括适应度值分类的K-means聚类实现任务分配、黏菌算法提高整体搜索效率、头脑风暴算法机器人内进行局部更新操作和机器人间进行全局更新操作完成重规划操作、交叉操作和大规模邻域搜索操作用以更新个体.实验结果表明:基于混合算法的任务均衡规划方法能够均衡规划多机器人任务,优化任务规划结果,提升任务的完成效率.
Based on the analysis of the problem of unbalanced tasks completed by robots
a planning algorithm based on hybrid algorithm is proposed. It includes fitness value classification of K-means clustering for task allocation
slime mold algorithm to improve the overall search efficiency
brainstorming algorithm for local update operation in robot and global update operation in robot for re-planning operation
crossover operation and large-scale neighborhood search operation to update individuals. The experimental results show that the task balancing planning method based on hybrid algorithm can balance multi-robot tasks
improve task planning results and improve task completion efficiency.
卢厚清,王辉东,黄杰,等.任务均分的多旅行商问题[J].系统工程, 2005, 23(2):19-21.
熊衍捷,高镇,李根.基于谱聚类的Baa S资源负载均衡调度算法[J].重庆大学学报, 2021, 44(11):40-47.
毛科技,孙俊生,颜世航.一种能耗均衡的WSNs层次路由协议研究[J].传感器与微系统, 2020, 39(1):18-21+25.
姚泽玮,林嘉雯,胡俊钦,等.基于PSO-GA的多边缘负载均衡方法[J].计算机科学, 2021, 48(S2):456-463.
董亚倩,杨帆,翟艺颖.考虑执行任务均衡的仓储多自动引导车路径优化方法[J].制造业自动化, 2021, 43(12):62-65.
罗海峰.基于混合局部搜索方法的大规模车辆路由问题求解研究[J].安徽职业技术学院学报, 2019, 18(2):5-8.
胡士娟,鲁海燕,黄洋,等.求解工作量平衡多旅行商问题的改进遗传算法[J].计算机工程与应用, 2019, 55(17):150-155+231.
张硕航,郭改枝.多旅行商模型及其应用研究综述[J].计算机科学与探索, 2022, 16(7):1516-1528.
VENKATESH P, SINGH A. Two metaheuristic approaches for the multiple traveling salesperson problem[J]. Applied Soft Computing, 2015, 26:74-89.
李道全,魏艳婷,张玉霞,等.基于改进蚁群算法的WSN能量均衡路由算法[J].计算机工程与应用, 2019, 55(17):117-124.
BERNARDINO R, PAIAS A. Heuristic approaches for the family traveling salesman problem[J]. International Transactions in Operational Research, 2021, 28(1):262-295.
BEKTAS T. The multiple traveling salesman problem:an overview of formulations and solution procedures[J]. Omega, 2006,34(3):209-219.
LI S, CHEN H, WANG M, et al. Slime mould algorithm:a new method for stochastic optimization[J]. Future Generation Computer Systems, 2020, 111:300-323.
XU X, CHEN H L. Adaptive computational chemotaxis based on field in bacterial foraging optimization[J]. Soft Computing, 2014,18(4):797-807.
NAKAGAKI T, YAMADA H, TOTHA. Maze-solving by an amoeboid organism[J]. Nature, 2000, 407(6803):470.
JOHANNSON A, ZOU J. A slime mold solver for linear programming problems[C]//Conference on Computability in Europe.Cambridge:Springer, 2012.
KE L. A brain storm optimization approach for the cumulative capacitated vehicle routing problem[J]. Memetic Computing, 2018,10(4):411-421.
李蒙蒙,秦伟,刘艺,等.结合头脑风暴优化的混合蚁群优化算法[J].计算机应用, 2021, 41(8):2412-2417.
XUE Y, ZHANG Q, ZHAO Y. An improved brain storm optimization algorithm with new solution generation strategies for classification[J]. Engineering Applications of Artificial Intelligence, 2022, 110:104677.
南丽君,陈彦如,张宗成.改进的自适应大规模邻域搜索算法求解动态需求的混合车辆路径问题[J].计算机应用研究, 2021,38(10):2926-2934.
陈嘉朋,张宏立,王聪,等.改进狼群算法求解多目标柔性作业车间调度问题[J].新疆大学学报(自然科学版)(中英文), 2022,39(1):42-48+73.
WANG Y Z, CHEN Y, LIN Y. Memetic algorithm based on sequential variable neighborhood descent for the minmax multiple traveling salesman problem[J]. Computers&Industrial Engineering, 2017, 106:105-122.
聂清彬,蔡婷,张莉萍,等.一种面向成本驱动的云资源调度策略研究[J].新疆大学学报(自然科学版), 2016, 33(4):454-458.
岳倩宇.多机器人任务规划方法研究[D].天津:天津大学, 2018.
高平安,蔡自兴,余伶俐.多移动机器人负载均衡任务规划算法[J].高技术通讯, 2009, 19(5):501-505.
0
浏览量
132
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621
