V. Charles

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Fractional programming deals with the optimization of one or several ratios of functions subject to constraints. Most of these optimization problems are not convex while some of them are still generalised convex. After about forty years of research, well over one thousand articles have appeared on applications, theory and solution methods for various types(More)
Probabilistic or Stochastic programming is a framework for modeling optimization problems that involve uncertainty. The basic idea used in solving stochastic optimization problems has so far been to convert a stochastic model into an equivalent deterministic model and is possible when the right hand side resource vector follows some specific distributions(More)
Hippocampal slices maintained in an oxygen-rich static interface chamber remained viable, as determined by the mitochondrial marker 2,3,5-triphenyltetrazolium chloride (TTC), for over 20 h in vitro. By contrast, slices exposed, after 1 h in vitro, to an anoxic environment for 25 min and then allowed to recover for 1-18 h, showed an initial slight decrease(More)
Non-Linear Stochastic Fractional programming models provide numerous insights into a wide variety of areas such as in financial derivatives. Portfolio optimization has been one of the important research fields in modern finance. The most important character within this optimization problem is the uncertainty of the future returns on assets. The objective of(More)
Keywords: Stochastic programming Fractional programming Multi-objective programming Redundancy a b s t r a c t Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in constraints and variables(More)
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