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Principle: Unlike most other DEA software, EMS does not use a heuristic in the conventional sense of the word. It calculates the penalty weights (and calculates them for a fixed K) by a reweighting of the data, that is, by modeling the data in linear regression form, as shown in Figure 1. For this process, EMS uses the connectionist MINIMAX (Nelder and Mead 1966) method to determine the optimal production combinations. This is a much better alternative to the heuristics that most other DEA software uses. The calculation is developed in an extremely efficient way by expressing the MINIMAX problem as a linear programming problem, and solving this problem using the direct LP technique of BPMPD developed by Csaba Mszros. In the following, we will give some details of the process of calculating the optimal production combinations and specify the linear programming problem that EMS uses to solve the MINIMAX problem.
INSIDE THE BPMPD LPP: This is also the basis of the linear programming problem that EMS uses to solve the MINIMAX problem. In this problem, the target function or grand objective denotes the sum of the weighted objectives, A2i = w,i Zi2i,i. To determine the optimal production combinations, one has to find a minimum of this function.
In order to find the optimal solution, we have to specify a "good" starting point for the MINIMAX process. For this purpose, EMS uses the same concept used to produce the starting round of solutions in EMS 1.0. If you have any suggestions for the addition of further data sets, please let us know :-). You can download EMS 1.3 from the following site: http://www.doe-solvers.org/emssuite-1.3.zip d2c66b5586
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