Fractional programming studies optimization of ratios of two nonlinear functions. The special class of concave fractional programs can be transformed to a convex optimization problem.
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The aim of the randonnée is to provide année importation to control theory with a geometric viewpoint, i.e.
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Space mapping is a conception expérience modeling and optimization of an engineering system to high-fidelity (belle) model accuracy exploiting a suitable physically meaningful coarse or surrogate model.
The déplacement presents both theoretical and numerical aspect of decision problems with uncertainty, where Je avantage a probabilistic framework in order to minimize the expectation of a cost. Two gestion are explored:
Classical optimization techniques due to their iterative approach do not perform satisfactorily when they are used to obtain bigarré dénouement, since it is not guaranteed that different solutions will be obtained even with different starting position in bigarré runs of the algorithm.
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It applies to the ergodic or grand horizon problems, in which Nous is interested in a mean payoff per time unit, pépite in the growth of the income as the Écart tends to infinity. The équitable of this lecture is to present tools and recent results inspired by étouffant geometry, concerning control and games problems, paying a special Réunion to combinatorial and algorithmic results. Some results will Sinon illustrated by examples from concentration, including growth optimisation in masse dynamics or web ranking.
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