Firms outperforming competitors often get their success through innovation and new technological knowledge acquisition. This study offers a Three-Stage decision-making model for acquiring the optimal time to invest. In first Stage, two competing firms decide invest in without knowing its level. next stage, will develop integrate it with knowledge. Due uncertainty of knowledge, stochastic progra...

We study a class of chance-constrained two-stage stochastic optimization problems where second-stage feasible recourse decisions incur additional cost. In addition, we propose a new model, where “recovery” decisions are made for the infeasible scenarios to obtain feasible solutions to a relaxed second-stage problem. We develop decomposition algorithms with specialized optimality and feasibility...

Stochastic programming deals with optimization under uncertainty. A stochastic programming problem with recourse is referred to as a two-stage stochastic problem. We consider the stochastic programming problem with simple integer recourse in which the value of the recourse variable is restricted to a multiple of a nonnegative integer. The algorithm of a dynamic slope scaling procedure to solve ...

Moment robust optimization models formulate a stochastic problem with an uncertain probability distribution of parameters described by its moments. In this paper we study a two-stage stochastic convex programming model using moments to define the probability ambiguity set for the objective function coefficients in both stages. A decomposition based algorithm is given. We show that this two-stag...

We consider the other direction: the 2-stage stochastic programming problem (or also called stochastic recourse problem). Conceptually one should think of the decision process taking place in two stages. In the first, values for the first stage variables x are chosen. In the second, upon a realisation of the random parameters, a recourse action is to be taken in case of infeasibilities. Costs a...

This paper applies two-stage stochastic quadratic programming to optimize conjunctive use operations of groundwater pumping and artificial recharge with farmer’s expected revenue and cropping decisions. The two-stage programming approach allows modeling of water and permanent crop production decisions, with recourse for uncertain conditions of hydrology, annual crops, and irrigation technology ...