It is worthwhile to discuss alternatives of treating laboratory constraints. A computationally equivalent treatment of work shifts is to introduce pre-scheduled "placeholder" operations that occupy gaps between work shifts. While the capacity constraint can be modeled by splitting multi-capacity modules into multiple single-capacity modules, this increases the size of M, thus increases the number of all constraints indexed by m. This is expected to be less computationally efficient than introducing capacity constraints explicitly as in equation ( ). Feasible solutions that comply with lag time constraints can be selected from a set of potential solutions (e.g., the heuristic method by Aarts et al. ), however, it is more computationally efficient to encode these as linear constraints than to select solutions from a less constrained problem in linear programming.