By Raquel J. Fonseca, Gerhard-Wilhelm Weber, João Telhada
This quantity comprises contributions from the eleventh overseas convention on administration technology (CMS 2014), held at Lisbon, Portugal, on might 29-31, 2014. Its contents replicate the huge scope of administration technological know-how, masking varied theoretical elements for a rather diversified set of purposes. Computational administration technology offers a distinct standpoint in proper decision-making techniques by way of targeting all its computational facets. those contain computational economics, finance and information; strength; scheduling; offer chains; layout, research and functions of optimization algorithms; deterministic, dynamic, stochastic, powerful and combinatorial optimization types; resolution algorithms, studying and forecasting resembling neural networks and genetic algorithms; versions and instruments of data acquisition, comparable to information mining; and all different subject matters in administration technological know-how with the emphasis on computational paradigms.
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Zéphyr ( ) • P. F. ca P. J. Fonseca et al. 1007/978-3-319-20430-7_5 31 32 L. Zéphyr et al. Dynamic Programming [8, 10], Reinforcement Learning [1, 6], Neuro-Dynamic Programming [2, 3], Approximate Dynamic Programming . In classical Dynamic Programming works, the value function is computed over a regular grid. Our approach is based on a simplicial partitioning of the state space, inducing a finite grid of points. The actual value function is computed over such grid points and, under convexity assumptions, extended as lower and upper bounds over the state space’s continuum.