人力资源分配问题是将若干个人力资源合理分配给若干个工作任务，从而达到人力生产效率最大化与人力生产成本最小化。文中提出一种改进的多目标和声搜索(MOIHS)算法来求解人力资源分配问题。 MOIHS算法是通过改变记忆考虑的选择机制与微调概率来改进基本的和声算法提高算法收敛稳定性，并采用快速非支配排序方法与建立动态拥挤的距离来获得一个分布良好的Pareto解集。在求解人力资源分配问题时，同时优化人力生产成本最小化与效率最大化两个目标，最后通过一个实例可以得到在解决该问题上多目标改进和声搜索算法优于多目标遗传算法，求出的解集也具有良好的分布性。%The human resource allocation problem seeks to find the expected objectives by allocating the limited amount of resource to va-rious activates. In this paper,a new multi-objective improved harmony search (MOIHS) has been proposed and applied to human re-source allocation problem to simultaneously optimize two goals about the cost minimization and efficiency maximization. MOIHS im-proves the base harmony search by changing the selection mechanism of memory consideration and the fine-tuning probability. It also u-ses the rapid non-dominate sorting method and establishes the dynamic crowded distance to get a good distribution of Pareto solution set. The experiment results show that,the improved harmony search is better than genetic algorithm for multi-objective resource allocation problem,it is able to give a well distributed Pareto-optimal solution.
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