基于离散多目标优化粒子群算法的多移动代理协作规划

无线传感器网络中多移动代理协作能快速高效地完成感知数据汇聚任务，但是随着移动代理访问数据源节点数的增加，移动代理携带的数据分组会逐渐增大，导致传感器节点能量负载不均衡，部分数据源节点能耗过快，网络生存期缩短。目前，针对该问题所设计的能耗均衡算法，多以降低多移动代理总能耗为目标，却未充分考虑部分数据源节点能量消耗过快对网络生存期造成的影响。提出离散多目标优化粒子群算法，以网络的总能耗和移动代理负载均衡作为适应度函数，在多移动代理协作路径规划中寻求近似最优解。通过仿真实验验证，所提出的多移动代理协作路径规划，在网络总能耗和网络生存期方面的性能优于同类其他算法。

Discrete multi-objective optimization of particle swarm optimizer algorithm for multi-agents collaborative planning

Although multiple mobile agents (MA) collaboration can quickly and efficiently complete data aggregation in wireless sensor network, the MA carrying data packages extensively increase along with a raise in the number of data source nodes accessed by MA, which causes unbalanced energy load of sensor nodes, high energy consumption of partial source nodes, and shortened lifetime of networks. The existing related works mainly focus on the objective of decreasing total energy consumption of multiple MA, without considering that rapidly energy consumption of partial source nodes has a negative effect on networks lifetime. Therefore, discrete multi-objective optimization of particle swarm algorithm was proposed, which used the total network energy consumption and mobile agent load balancing as fitness function for the approximate optimal itinerary plan in multiple mobile agent collaboration. Furthermore, the simulation result of the proposed algorithm is better than the similar algorithm in total energy consumption and network lifetime.