In many practical engineering design and other scientific optimization problems, the objective function is not given in closed form in terms of the design variables. Given the value of the design variables, the value of the objective function is obtained by some numerical analysis, such as structural analysis, fluidmechanic analysis, thermodynamic analysis, and so on. It may even be obtained by...

This expository article discusses approaches for modeling optimization problems that involve uncertainty. The emphasis of the paper is on motivation and intuition rather than technical completeness. By virtue of its length, the paper is inevitably incomplete, and the reader is advised to look at other papers in this encyclopedia to explore the richness of modeling approaches that this paper can...

We present a novel paradigm for the computational modeling of speech timing. Our approach is based on two core assumptions: (1) the organization of speech is governed by the resolution of trade-offs between production and perception demands, and (2) isochrony at the syllable and stress group level, while not measurable in absolute terms in the speech signal, is present in a language-specific ma...

This paper surveys the most recent advances in the context of decision making under uncertainty, with an emphasis on the modeling of risk-averse preferences using the apparatus of axiomatically defined risk functionals, such as coherent measures of risk and deviation measures, and their connection to utility theory, stochastic dominance, and other more established methods. © 2010 Elsevier Ltd. ...

Optimization of Supply Chains: A Continuous Approach Ciro D’Apice, Simone Göttlich, Michael Herty, and Benedetto Piccoli This book offers a state-of-the-art introduction to the mathematical theory of supply chain networks, focusing on those described by partial differential equations. The authors discuss modeling of complex supply networks as well as their mathematical theory; explore modeling,...

The recent advances in genetic engineering, high powered computing and global optimization continue to stimulate interest in the area of molecular modeling and protein structure prediction. The goal of these eeorts is the ability to correctly predict native protein conformations and the binding interactions of macromolecules. These two problems currently dominate the eld of computational chemis...

Abstract – Resource allocation and scheduling optimization problems are core problems in the field of IT systems. However, such problems frequently underlie several additional constraints. The formalization of a real life problem requires a well-defined mathematical and modeling approach providing an integrated verification and optimization. The current paper proposes such methods adapting Proc...

We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way that preserves fast linear transforms in the original problem. By representing linear functions in the transformation process not as matrices, but as graphs that encode composition of linear operators...

A considerable amount of optimization problems arising in the control and systems theory field can be seen as special instances of robust optimization. Much of the modeling effort in these cases is spent on converting an uncertain problem to a robust counterpart without uncertainty. Since many of these conversions follow standard procedures, it is amenable to software support. This paper presen...