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The rotating workforce scheduling problem involves the construction of an efficient sequence of work and rest periods spanning over a number of weeks. This schedule must satisfy the workforce requirements during the different shifts of each day and conform to all the other conditions imposed on the workhest periods and their sequence. We consider the modeling of the rotating workforce scheduling problem as a network flow problem. All the constraints on the problem are incorporated in the network itself, except for the staff-covering constraints that are treated as side constraints. The optimal solution to the problem corresponds to a path in the network and is identified using a dual-based approach. The model deals with the issues of rest-period identification, worklrest period sequencing, and shift scheduling simultaneously and is designed to handle multiple shift cases with time-varying demands. The procedure, which is capable of solving large-scale problems, is applied to three well-known problems in rotating workforce scheduling. The computational results presented indicate that this procedure provides a useful method for solving large-scale complex problems in workforce scheduling.

In this paper, we study the capacity allocation problem faced by make-to-order manufacturing f m s encountering expected total demand in excess of available capacity. Specifically, we focus on fms' manufacturing short-life-cycle or seasonal products such as high fashion apparel. Using a decision-theory-based approach, we develop a capacity allocation policy that allows such firms to discriminate between two classes of products (one yielding a higher profit contribution per unit of capacity allocated to it than the other), resulting in selective rejection of orders for the class with the lower unit contribution. The effectiveness of capacity rationing is investigated under a wide array of conditions characterized by variations in factors such as the ratio of unit profit contributions of the two product classes, the mtio of total available capacity to expected total demand, the ratio of expected demands between the two classes, and the variability in demand for each product class. The results indicate that capacity rationing is very effective in increasing the total profit, and could therefore serve as a valuable decision tool for managers in such fms.