基于多阶段遗传算法的人力资源管理

Human resource management based on a multi-stage genetic algorithm

针对企业的员工雇佣计划的优化问题,根据实际中遴选雇佣员工存在一定程度的随机性特点,以按期完成项目、消耗成本最低为目标,采取优胜劣汰策略,利用随机规划方法构建雇佣计划的优化模型;将遗传算法与多阶段决策相结合设计了模型的求解算法;最后通过算例对模型及算法的有效性进行了验证.计算结果表明:提出的方法能够通过合理控制不同时段聘用,及解聘的数量逐步提高雇佣员工的平均工作能力,员工平均工作能力提高幅度达到41%,从而实现了针对项目的人力资源优化.

This research in accordance with the actual selection of employees employs a certain degree of random-ness features to complete the project on schedule by optimization for the enterprise＇ s employment plan. First, it takes the lowest consumption and costs as the goal, and constructs a stochastic programming model based on the survival of the fittest strategy to optimize the employment plan. Second, it works out an algorithm for the model by integrating the genetic algorithm with a multi - stage decision - making strategy ; finally, it proves the validity of the model and the algorithm with some examples. The results show that the proposed method can be used for employ-ment and dismissals at different times through a rational control, which can gradually improve the average working ability of the employees up to 41% and achieve the optimization of the targeted human resources.