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The results which are obtained, are compared to those reached using a conventional mathematical optimization procedure, also coupled to the process simulator.
Further, the use of cost functions would allow the application of any mathematical optimization procedure to maximize the savings, without the use of exergy or exergoeconomics.
The advanced exergoeconomic method does not constitute a mathematical optimization procedure, but defines the best possible design as one at which the advanced exergoeconomic factors for all components are 50%%.
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A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios.
Numerical optimization procedure using the desirability approach was used to develop an optimized formulation and thereby validate the mathematical models generated.
Numerical optimization procedures are discussed.
Three sequential mathematical models and related optimization procedure to optimize regeneration reuse water networks are proposed.
In mathematics, mathematical optimization (or optimization or mathematical programming) refers to the selection of a best element from some set of available alternatives.
A parametric study of the mechanism performance is performed, based on the mathematical model, and an optimization procedure is proposed, based on Lagrange's multipliers and Kuhn Tucker conditions, which identifies the design vector that maximizes the performance of these flexure-based compliant mechanisms.
While fixed costs are, under a constrained budget, decisive to the resources left for allocating measurements, they cancel out in the course of the mathematical differentiation associated with the optimization procedure, and thus will not affect the eventual optimal allocation strategy [ 43].
This leaves us to include these material uncertainties into the mathematical model and thus into the optimization procedure in order to achieve a robust design.
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