基于遗传算法的参与式感知激励机制的优化

The Optimization of Incentive Mechanism in Participatory Sensing Based on Genetic Algorithm

以最大化有效参与者数量和最大化感知区域覆盖率为优化目标,以服务提供者的有限预算为约束,建立参与式感知激励机制多目标优化模型,运用遗传算法对模型求最优解。同经典激励机制优化方法 RADP-VPC-RC和GIA在相同参数条件下的仿真结果进行对比,证实了遗传算法优化模型的有效性和优越性。

Establishing the multi-objective optimization model of incentive mechanism in participatory sensing. The optimization goal is making the effective participants most and making the rate of perception area lagest. The constraint is the limited budget of the service provider. Geting the optimal solution of the model by genetic algorithm. The comparison of the simulation results with the classic incentive mechanism optimization method RADP-VPC-RC and GIA under the condition of the same parameters,verifying that the genetic algorithm optimization model is more effective and superior.