This thesis explores the application of scenario planning to regional strategic transportation planning (RSTP). Like all strategic planning, RSTP takes place in the presence of uncertainty, requiring flexibility and systematic thinking. The work presented builds on that of Mufioz in his application of scenarios to Mendoza, Argentina and the Cooperative Mobility Program ReS/SITE team's scenario-...

Service industries, such as ports, are attentive to their standards, a smooth service flow and economic viability. Cost benefit analysis has proven itself as a useful tool to support this type of decision making; it has been used by businesses and governmental agencies for many years. In this book chapter we demonstrate different modelling methods that are used for estimating input factors requ...

Web allows learners to investigate any question with a great variety of Web resources, in which they could construct a wider, and deeper knowledge. In such investigative learning process, it is important for them to deepen and widen the question, which involves decomposing the question into the sub-questions to be further investigated. This corresponds to creating a learning scenario that impli...

OF THE DISSERTATION Two-Stage Portfolio Optimization with Higher-Order Conditional Measures of Risk by Sıtkı Gülten Dissertation Director: Dr. Andrzej Ruszczyński In this study, an application of novel risk modeling and optimization techniques to daily portfolio management will be described. In the first part, I develop and compare specialized methods for scenario generation and scenario tree c...

The first part of the paper briefly overviews the problem of gene and species trees reconciliation with the focus on defining and algorithmic construction of the evolutionary scenario. Basic ideas are discussed for the aspects of mapping definitions, costs of the mapping and evolutionary scenario, imposing time scales on a scenario, incorporating horizontal gene transfers, binarization and reco...

Dynamic Stochastic Optimization Models for Air Traffic Flow Management by Avijit Mukherjee Doctor of Philosophy in Engineering – Civil and Environmental Engineering University of California, Berkeley Professor Mark Hansen, Chair This dissertation presents dynamic stochastic optimization models for Air Traffic Flow Management (ATFM) that enables decisions to adapt to new information on evolving ...

This paper addresses a multistage stochastic model for the optimal operation of wind farm, pumped storage and thermal power plants. The output of the wind farm and the electrical demand are considered as two independent stochastic processes. The evolution of these processes over time is modeled as a scenario tree. Considering all possible realizations of stochastic process, leads to a huge set ...

We consider a reliable network design problem under uncertain edge failures. Our goal is to select a minimum-cost subset of edges in the network to connect multiple terminals together with high probability. This problem can be seen as a stochastic variant of the Steiner tree problem. We propose two scenario-based Steiner cut formulations, study the strength of the proposed valid inequalities, a...

Solving realistic dynamic asset allocation problems remains a challenge. While considerable progress with respect to theoretical insights has been made in the past years using dynamic programming, this technique is hardly applicable to deal with industry problems involving numerous sources of uncertainty and path-dependent variables. An alternative solution strategy that has been applied to var...

The main goal of this paper is to describe a new pruning method for solving decision trees and game trees. The pruning method for decision trees suggests a slight variant of decision trees that we call scenario trees. In scenario trees, we do not need a conditional probability for each edge emanating from a chance node. Instead, we require a joint probability for each path from the root node to...