This research introduces a new type of data envelopment analysis (DEA) model termed the optimal system design (OSD) DEA model. Conventional DEA models evaluate DMUs’ performances given their known input and output data. The OSD DEA models take this one step further. They optimally design a DMU’s resource allocation in terms of profit maximization given the DMU’s total available budget. The need to design optimal systems is quite common and is sometimes necessary in practice. In actual fact, this study demonstrates that through the OSD DEA models, we can provide DMUs with more information than optimal portfolios of resources such as optimal budgets and budget congestion, i.e., the more the budget is consumed, the less the maximal profit. The proposed OSD DEA models are linear programs, and thus can be solved by the standard LP solvers to obtain DMUs’ optimal designs. However, to derive the DMUs’ corresponding optimal budgets, and to verify if the DMUs provide evidence of budget congestion, we need to modify the solvers, which may not be trivial. Therefore, this study exploits the special structures of the models to develop a simple solution method that can directly not only derive both a DMU’s optimal design and optimal budget, but can also check for the existence of budget congestion.
