The solution of several operations research problems requires the creation of a quantitative
model. Sensitivity analysis is a crucial step in the model building and result communication …

A great deal of theoretical work exists on how to model and value investment opportunities
having real options. To date, this work has provided new insights into capital budgeting …

In this study, activated carbon was prepared from an abundant Egyptian agricultural waste
material (Corn Cob) through microwaves assisted activation. The effect of using two different …

Gathering the right kind and the right amount of information is crucial for any decision-
making process. This book presents a unified framework for assessing the value of potential …

This article develops a new approach for constructing causal maps called the Collective
Causal Mapping Methodology (CCMM). This methodology collects information …

In this paper, we review the role of probabilistic graphical models in artificial intelligence. We
start by giving an account of the early years when there was important controversy about the …

We provide a generic Monte Carlo method to find the alternative of maximum expected utility
in a decision analysis. We define an artificial distribution on the product space of alternatives …

Developed from the authors' longstanding course on decision and risk analysis, Value-
Added Decision Making for Managers explores the important interaction between decisions …

We introduce a subclass of chain event graphs that we call stratified chain event graphs, and
present a dynamic programming algorithm for the optimal selection of such chain event …

Influence diagrams have been important models for decision problems because of their
ability to both model a problem rigorously at its mathematical level and depict its high-level …