OPTIMIZING HIRING STRATEGIES: A DYNAMIC PROGRAMMING APPROACH TO CUTTING RECRUITMENT AND OVERSTAFFING COSTS

Abstract

The aim of this article is to develop a manpower planning model which incorporates fixed recruitment and overstaffing costs at each period of recruitment in order to evaluate total minimum manpower cost at the last period of a planning horizon. The proposed model in this research uses the backward approach which makes it to have lower suboptimal costs in between the stages compared to the existing models which use forward recursive method of dynamic programming. Although the minimum total of manpower cost is the same for both proposed and the existing model algorithms, the suboptimal costs in the proposed model are lower than the corresponding suboptimal manpower costs in the existing model. This is one of the advantages the proposed model has compared to other models in literature, making it possible for policy makers to detect periods where manpower in terms of numbers of staff and the skills needed early enough. Another advantage of the model algorithm is batch recruitment at certain periods of computation. This assists policy makers to carry out recruitment in batches instead of period by period. This will reduce recruitment cost and maximize organization’s efficiency and profit.