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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127(2), 89–98 (2001) 4. : Short-term hydrothermal generation scheduling model using a genetic algorithm. IEEE Trans. Power Syst. 18(4), 1256–1264 (2003) 5. : Optimizing operational policies of a korean multireservoir system using sampling stochastic dynamic programming with ensemble streamflow prediction. J. Water Resour. Plan. Manag. 133(1), 4–14 (2007) 6. : Stochastic optimization of multireservoir systems via reinforcement learning. Water Resour. Res. 43(11), W11408 (2007) 7. : Variable resolution discretization in optimal control.

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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 [9]. 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.

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