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Second-order conic programming for data envelopment analysis models
Abstract
Data envelopment analysis (DEA) is a widely used benchmarking technique. Its strength stems from the fact
that it can include several inputs and outputs of not necessarily the same type to evaluate efficiency scores.
Indeed, the aforesaid method is based on mathematical optimization. This paper constructs a second-order
conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the
former problem, and provides a MATLAB function associated with it. As far as known, no MATLAB
function solves DEA models. Among different types of DEA, this function can handle deterministic,
Malmquist index, and stochastic models. In fact, DEA is involved in various practical applications, thus, this
work will provide some possible future extensions, not only for MATLAB but also for any programming
software in applications of decision science and efficiency analysis.
Description
Keywords
Data envelopment analysis, Efficiency, Malmquist DEA, Stochastic DEA, MATLAB
functions, Numerical simulations, Mathematical models
Citation
Mourad, N. (2022) “Second-order conic programming for data envelopment analysis models,” Periodicals of Engineering and Natural Sciences (PEN), 10(2), p. 487.