华中科技大学学报（自然科学版）Issue(z1)：424-427,4.DOI:10.13245/j.hust.15S1101
基于混沌 QPSO 算法的多 AUVs 任务分配
Multiple AUVs task allocation based on chaotic QPSO algorithm
摘要
Abstract
Focusing on each node load imbalance problem of multiple autonomous underwater vehicles system(MAUVs)under the complicated conditions in the process of task allocation,chaos optimiza-tion QPSO algorithm was proposed.It was based on the searched current optimal position of quantum particle swarm,chaos factor was added to chaos QPSO algorithm and generated chaotic sequence.U-sing chaotic searching in chaos optimization,searching ergodicity property etc,which have similar function of collaborative learning operation,the particles of optimal location in the chaotic sequence replacing the current position of quantum particle swarm,making the approximate optimal breaking a-way from local optimum and getting the real global optimum.The experiment results show that chaos optimization QPSO algorithm in the process of multiple AUVs’task allocation,improving the accura-cy of the task allocation and optimization efficiency,bring task allocation up to global optimal value.关键词
混沌优化/量子粒子群/混沌量子粒子群/多水下机器人系统/任务分配Key words
chaos optimization/quantum-behaved particle swarm/chaotic quantum-behaved particle swarm/multiple autonomous underwater vehicle system/task allocation分类
信息技术与安全科学引用本文复制引用
李建军,张汝波,杨玉..基于混沌 QPSO 算法的多 AUVs 任务分配[J].华中科技大学学报（自然科学版）,2015,(z1):424-427,4.基金项目
国家自然科学基金资助项目（60975071，61100005）；教育部科学研究项目（13YJA790123）． （）
