Optimization of the Output of a Group of Proportionate Healthcare Equipment Manufacturing Plants

Abstract

Optimization is an important concept in decision making process and is thus a significant component of data envelopment analysis. A typical optimization process involves the minimization of a cost function and maximization of a fitness function. A classic example is in the manufacture of healthcare equipment such as sensors. In this chapter, the author presents an integrated study of the optimization and efficiencies of a group of healthcare equipment manufacturing plants which have some defined proportionate relationships as per their input resources and outputs (profits). Three approaches to the problem are discussed, namely standard linear programming problem (LPP), basic algebra and the machine learning principle of qualitative classification. Apart from stating and proving some new theorems, a report on some LPP numerical experiments carried out is presented using MATLAB version R2024b. Varieties of additional experiments may be initiated for further study.