Heuristics for workforce planning with worker differences
- 作者：John W. Fowler ; Pornsarun Wirojanagud ; Esma S. Gel
- 关键词：Workforce planning ; Cross-training ; Heuristics ; Genetic algorithms
- 刊名：European Journal of Operational Research
- 出版年：2008
- 期刊代码：58_03772217
- 类别：et
- 出版时间：1 November 2008
- 卷：190
- 期：3
- 页码：724-740
- 文件大小：204 K
摘要
This study considers decisions in workforce management assuming individual workers are inherently different as measured by general cognitive ability (GCA). A mixed integer programming (MIP) model that determines different staffing decisions (i.e., hire, cross-train, and fire) in order to minimize workforce related costs over multiple periods is described. Solving the MIP for a large problem instance size is computationally burdensome. In this paper, two linear programming (LP) based heuristics and a solution space partition approach are presented to reduce the computational time. A genetic algorithm was also implemented as an alternative method to obtain better solutions and for comparison to the heuristics proposed. The heuristics were applied to realistic manufacturing systems with a large number of machine groups. Experimental results shows that performance of the LP based heuristics performance are surprisingly good and indicate that the heuristics can solve large problem instances effectively with reasonable computational effort.