Monthly tour scheduling models with mixed skills considering weekend off requirements

Unlike manufacturing, where standard shifts and days off are the rule, the service industry operates every day of the week across a month and a year. To maintain the morale and productivity of the workers in the service industry, the weekend off requirements, one of the important work preferences for the workers, should be respected and balanced for a longer planning horizon beyond a week. This paper deals with the monthly tour scheduling problem with mixed skills considering the weekend off requirements in contrast to the weekly planning horizon that is typical in most literature. The objective is to obtain the most economical mix of types of workers satisfying the patterns of demands for the workers and desired work characteristics. Two model formulations are developed based on implicit programming techniques. One model uses a general integer programming (GIP) formulation and assigns the lunch break hours aggregately to the workers based on the worker types. The other one adopts a binary integer programming (BIP) formulation and assigns the lunch break hours explicitly to the individual workers. The effectiveness of the two models is illustrated by the numerical tests and the results show that the BIP formulation is more efficient than the GIP formulation.