Metode Branch and Bound Untuk Menyelesaikan Program Stokastik Cacah Campuran Dua Tahap

Abstract

The Stochastic Programming that deals with optimization of decision maker with available uncertainty in problem data from the following times, The objeck type of discuses is random optimization problems in wich out come of random data inplicite on going time, and dicisions will be optimal doesn’t have to anticipative next result (non-antisipative). This relates to optimization ‘real time’ that shaw as needs of optimal decisions * here-and-now’ in uncertainty incomplete in virontment data. If probabilistics information it available, the suitable operational models of optimization ‘real time’ can be formulated as multi-stage stochastic programming. Essentially this model is proposed to change deterministic, in which the uncertain parameters coefisien is random independent distribution probability of decisions variable. Under two-stage stochastic programming paradigm, the decision variables are portioned into two set. The finit-stage variables are those that have to be decided before the actual realizations of the uncertain parameters. Subsequently, once the random events have presented themselves, futher design or operasional policy improvements can be made by selection, at certain cost, the values of the second stage or recourse variable,