Multistage material-handling (MSMH) processes are broadly possessed by industries for manufacturing massive amounts of workpieces (jobs), where hoists are usually employed by following certain movement schedules based on the job-processing recipes. In this paper, we consider a common situation that an existing MSMH production line has reached its maximum productivity; in order to debottleneck the production and increase its productivity, some units will be retrofitted to increase their job-processing capacity under a fixed budget. Under this situation, which units need to be retrofitted and how many additional capacities will be added to those retrofitted units have to be optimally determined. Correspondingly, since process design has changed, the hoist schedule also needs to be adjusted. Apparently, the best way to deal with such an MSMH debottleneck problem requires the consideration of both the process retrofit and hoist rescheduling at the same time. In this paper, an MILP (mixed integer linear programming) based model is developed to simultaneously identify the best retrofit design and hoist schedule to obtain the maximum productivity under a fixed retrofit budget. On the basis of this development, different retrofit and hoist-scheduling scenarios under different budgets can also be examined, so that the Pareto frontier balancing both retrofit investment and productivity can be identified, which will provide the comprehensive decision support for an MSMH debottleneck problem. The efficacy of the proposed methodology has been demonstrated by case studies.