WSN中基于PSO的多约束Steiner树优化算法

Multiple-Constraint Steiner Tree Optimization Algorithm in WSN Based on PSO

中文关键词:  无线传感器网络  跳跃粒子群  双层编码  多目标约束Steiner树

英文关键词:wireless sensor network(WSN)  jump particle swarm  double layer encoding  multiple-constraint Steiner tree

中文摘要:

      针对多目标约束的Steiner树问题（MCSTP,multi-constraint Steiner tree problem），提出一种基于双层编码机制和跳跃粒子群优化(JPSO)的启发式算法（JPSO-DE），来构建最优树结构。首先，选择总能耗、网络寿命、收敛时间和通信干扰作为优化约束目标；然后，根据提出的双层编码方案对生成树的解进行编码，同时利用跳跃粒子群优化算法来寻找帕累托最优解；最后，利用提出的混合适应度函数找出近似最优树结构。仿真实验表明，JPSO-DE方法可以产生近似最优的树结构，具有高效性和可行性。

英文摘要:

      To solve the problem of multi-constraint Steiner tree problem (MCSTP),a heuristic algorithm (JPSO-DE) based on double layer encoding mechanism and jump particle swarm optimization (JPSO) algorithm is proposed,which is used to construct the optimal tree structure.Firstly,JPSO-DE selects the total energy consumption,network lifetime,convergence time and the communication interference as the optimization goals.Secondly,it uses the double layer encoding scheme to encode the tree,and uses jump particle swarm optimization algorithm to find the Pareto optimal solution.Finally,it uses hybrid fitness function to find the near-optimal tree structure.The simulation results show that JPSO-DE can generate near-optimal tree structure with high efficiency and feasibility.