Aggregate planning in crew-loaded production environments

Virtually all existing optimization techniques for the aggregate planning problem incorporate continuous decision variables. However, predetermined shift settings in crew-loaded production operations often require the decision variables to be discrete values. Consequently, currently available optimization methods are not appropriate for discrete production environments. This paper describes an optimal mixed-integer programming formulation for the aggregate planning problem that explicitly specifles discrete variables, thus resulting in feasible workforce levels for crew-loaded production environments. The mixed integer model is compared to the LDR, the Production Switching Heuristic and then to PSR. An application at Owens-Corning Fiberglas is also presented.