Abstract
This chapter presents a view of the recent operational methods of stochastic programming and discusses their applications to static and dynamic economic problems. It discusses the general framework of economic model specifications using programming methods and a general survey and appraisal of the current state of the theory of applied stochastic programming. The chapter reviews economic applications from an empirical standpoint, highlighting the following elements: (1) the implications of the statistical distribution of the maxim and in terms of the mean variance characteristics, (2) the decision rule theory of operations research under the chance-constrained model, and (3) a new method of incorporating reliability measures into a systems reliability model. It presents models for market equilibrium under alternative types of markets characterized by the activity vectors constrained by various decision rules subject to risk-aversion, diversification, and decentralization.
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