Using the k-Chaining Approach to Solve a Stochastic Days-Off-Scheduling Problem in a Retail Store

The present study addresses the personnel assignment and scheduling problems through the multiskilling flexibility strategy with the aim of reducing the negative impacts on a company’s cost structure that come as a result of demand uncertainty. The personnel assignment matter is handled using the chaining approach and it is evaluated whether a multiskilled workforce that minimizes the expected costs associated with training and under/overstaffing can be planned while taking into account demand uncertainty and using the k-chaining policy for a days-off scheduling problem. Until now, literature’s main focus has been 2-chaining policies, where every multiskilled employee is at most trained in two departments, i.e., k = 2. Hence, this research intends to determine scenarios where a k-chaining policy with k ≥ 2 offers more cost-effective multiskilling structures than a 2-chaining one. Initially, a deterministic mixed-integer linear optimization model is developed and then modified into a two-stage stochastic optimization model in order to add demand uncertainty. Such methodology is subsequently applied to a Chilean retail store where a Monte Carlo simulation is used to generate different daily demand scenarios. The results obtained suggest that with high levels of demand variability k-chaining policies seem favorable. Nonetheless, none of the employees evaluated were able to work in more than three departments, which leads to the conclusion that it does not appear to be advantageous to implement excessive flexibility levels.