Program Stokastik Cacah Campuran Dua Tahap
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Stochastic program is a tool for planning and optimal decision making with uncertainty in the data. Type object of study is a random optimization problem in which the results (outcomes) of random data is not revealed at run time, and the decision should be optimized not anticipate future results. This provides a close connection with the optimization of ”real time” needed for optimal decision ”here and now” in the data environment uncertain. In this study proposes a new approach to obtaining global optimization model of problem nonlinear mixed-integer stochastic. The research focuses on to-stage stochastic problems ith lack of nonlinearity present in the objective function and constraints. The first stage is orth counting variable while the second stage variable campurah chopped and continuous. The issue is formulated by representation based scenarios. The basic idea to resolve the probelm of nonlinear mix-integer stochastic program is to transform the model into a model equivalent in the form of mixinteger nonlinear deterministic program. This is possible because the uncertainty is assumed to be spread discrete, can be modeled as a finite number of scenarios. However, the size of the equivalent model will grow rapidly as a consequence of a number of scenarios and the amount of time horizon. So that the number of scenarios can be limited (finite) necessary engineering formation scenarios. Filterred probability space concept combined with data mining will be used for the formation of scenarios. So that to acquire problem solving meghod program-mix minced no large-scale linear convexity approach can be used in order to obtain a global optimal solution.
- PD - Mathematics