摘要
针对求解最优联盟结构时搜索空间大、效用低等问题,提出了一种基于离散最近过去位置更新策略的多进制离散粒子群优化(MDPSO-DRPPUS)算法。首先,使用基于索引的编码方式编码联盟结构。其次,将多目标优化问题转化为联盟结构的特征值函数。最后,使用MDPSO-DRPPUS算法进行最优联盟结构的搜索。实验表明,与多进制离散粒子群优化(MDPSO)算法和遗传算法(GA)相比,所提算法运行时间大幅度降低,联盟结构的效益、均衡性和边缘节点的完成任务效率都有所提高。
A discrete recent past-position updating strategy based m-ary discrete particle swarm optimization(MDPSO-DRPPUS)algorithm was proposed for the problem of large search space and low efficiency when solving the optimal coalition structure.First,the coalition structure with index-based was coded.Then,the multi-objective optimization problem was transformed into an eigenvalue function of the coalition structure.Finally,the optimal coalition structure was searched by using the MDPSO-DRPPUS algorithm.Experiments show that compared with the m-ary discrete particle swarm optimization(MDPSO)algorithm and genetic algorithm(GA),the proposed algorithm dramatically reduces the average running time,and improves the efficiency and equilibrium of the coalition structure and task completion efficiency of edge nodes.
作者
赵庶旭
韦萍
王小龙
ZHAO Shuxu;WEI Ping;WANG Xiaolong(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730071,China)
出处
《通信学报》
EI
CSCD
北大核心
2023年第2期172-184,共13页
Journal on Communications
基金
甘肃省重点研发计划基金资助项目(No.20YF8GA123)。
