We adopt Benders’ decomposition algorithm to solve scenariobased Stochastic Constraint Programs (SCPs) with linear recourse. Rather than attempting to solve SCPs via a monolithic model, we show that one can iteratively solve a collection of smaller sub-problems and arrive at a solution to the entire problem. In this approach, decision variables corresponding to the initial stage and linear reco...

Mohammad Hossein Hakimi Meibody was born in 1963 in Meibod, Yazd province. He gets his diploma in Meibod and then for higher education, he went to Isfahan university and exceeded direction of plant science for 4 years and graduated in 1989 with excellent grade. Then, he went to Tehran university and passed course of Plant Systematic in Biology department of faculty of science since 1996 with ex...

In this paper, we consider an adaptive approach to address optimization problems with uncertain cost parameters. Here, the decision maker selects an initial decision, observes the realization of the uncertain cost parameters, and then is permitted to modify the initial decision. We treat the uncertainty using the framework of robust optimization in which uncertain parameters lie within a given ...

An assay technique, homogeneous enzyme immunoassay, is described for the quantitative determination of morphine derivatives in biological fluids. An enzyme is labeled with morphine. When the enzymelabeled morphine is bound by antimorphine antibodies, the enzyme is rendered inactive. Free morphine competes with enzyme-morphine for antibody binding sites preventing inhibition of enzyme activity. ...

We consider quadratic stochastic programs with random recourse — a class of problems which is perceived to be computationally demanding. Instead of using mainstream scenario tree-based techniques, we reduce computational complexity by restricting the space of recourse decisions to those linear and quadratic in the observations, thereby obtaining an upper bound on the original problem. To estima...

In this paper, we introduce a class of stochastic programming problem with fixed charge recourse in which a fixed cost is imposed if the value of the continuous recourse variable is strictly positive. The algorithm of a branch-and-cut method to solve the problem is developed by using the property of the expected recourse function. Then, the problem is applied to a power generating system. The n...

Existing complexity results in stochastic linear programming using the Turing model depend only on problem dimensionality. We apply techniques from the information-based complexity literature to show that the smoothness of the recourse function is just as important. We derive approximation error bounds for the recourse function of two-stage stochastic linear programs and show that their worst c...