MODIFIKASI LAGRANGIAN AUGMENTED UNTUK PROGRAM NONLINIER STOKASTIK MULTI-TAHAP
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Date
2014-05-22
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Abstract
Multi-stage stochastic programming problems arise in many practical situations, such as production
and manpower planning, portfolio selections and so on. This paper describes our efforts to develop
a nonlinear programming algorithm for problems characterized by a large sparse set of linear
constraints and a significant degree of nonlinearity in the objective function. It has been our
experience that many linear programming problems are inordinately large because they are
attempting to approximate, by piecewise linearization, what is essentially a nonlinear problem. It
also appears that many real-life problems are such that only a small percentage of the variables are
involved nonlinearly in the objective function
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multi-stage stochastic nonlinear programs, projected Lagrange, scenario analysis, decomposition