This paper presents the client-servlet-coprocess interaction model, a new form of the client-server model. The client-servlet-coprocess model uses an HTTP Java servlet to specialize a servlet-enabled Web server to provide on-line client sessions with an interactive program run as a coprocess for the servlet. This model is designed for experimenting online with prototypical implementations of th...

Over the last two decades, robust optimization has emerged as a computationally attractive approach to formulate and solve single-stage decision problems affected by uncertainty. More recently, robust optimization has been successfully applied to multi-stage problems with continuous recourse. This paper takes a step towards extending the robust optimization methodology to problems with integer ...

Some recent developments in the area of risk aversion in stochastic integer programming are surveyed. After a discussion of modeling guidelines and resulting mean-risk stochastic integer programs emphasis is placed on structural properties of these optimization problems and on algoritms for their solution. Bibliographical notes conclude the paper.

Credit scoring models have been widely studied in the areas of statistics, machine learning, and artificial intelligence (AI). Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. Since an improvement in accuracy of a fraction of a percent might translate into significant savings, a m...

This talk discusses some modeling and solution methods for the problem of pre‐disaster transportation network protection against uncertain future disasters. Given limited resources, the goal of the central planner is to choose the best set of network components to protect while allowing the network users to follow their own best perceived routes in any resultant network configuration. This prob...

We propose a new variant of the two-stage recourse model. It can be used e.g., in managing resources in whose supply random interruptions may occur. Oil and natural gas are examples for such resources. Constraints in the resulting stochastic programming problems can be regarded as generalizations of integrated chance constraints. For the solution of such problems, we propose a new decomposition...

Stochastic integer programming problems combine the difficulty of stochastic programming with integer programming. In this article, we briefly review some of the challenges in solving two-stage stochastic integer programming problems, and discuss the research progress towards these challenges.

A new class of fuzzy stochastic optimization models—two-stage fuzzy stochastic programming with Value-at-Risk (FSP-VaR) criteria is built in this paper. Some properties of the two-stage FSP-VaR, such as value of perfect information (VPI), value of fuzzy random solution (VFRS), and bounds of the fuzzy random solution, are discussed. An Approximation Algorithm is proposed to compute the VaR by co...

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate secondstage policies here-and-now and implement the best of these policies once the uncertain parameters have been observed. We analyze the approximation quality and the computational complexity of the K-adaptability proble...