Applied Decision Science for Discerning Decision Makers
Decision Modeling discusses the principles of rational decision making and formulation of competitive strategy from a system-analytic perspective. The aim is to contribute to the advancement of managerial competence by disseminating a theoretically sound foundation of knowledge geared to enhance professionalism, expertise and prudent foresight.
The philosophical basis espoused in this website asserts that the interdisciplinary framework which characterizes the field of systems analysis, when properly employed, provides accurate representations of decision and strategy problems, promotes a thorough understanding of the fundamental issues underlying those problems, facilitates systematic risk assessment of alternative courses of action, and expedites the identification, evaluation, selection and subsequent implementation of practicable optimum solutions.
Systems analysis is, in essence, a logical approach to problem solving encompassing a wide range of specialized tools derived from a variety of scientific disciplines. It enjoys a proven track record in prescribing effective design parameters, efficient operational guidelines, and optimal control methods for all manner of challenging systems imbued with technical and administrative complexity, including the Apollo moon program. When applied to the analysis of important decisions, system-analytic modeling complements and enriches judgment and intuition, thereby increasing the level of confidence associated with the decision-making process. Modeling yields insight. Progressive decision makers are wise to avail themselves of the comprehensive worldview and powerful problem-solving resources afforded by decision modeling.
The material discussed in this website presupposes familiarity with college-level algebra and coordinate geometry. Prior exposure to probability theory is desirable; however, a review of the basic concepts of probability is included in the Probability Theory review module. Knowledge of linear algebra and calculus should prove beneficial but, with the exception of certain optional material, is not required. See also Wikipedia articles: Algebra, Analytic Geometry, Probability, Probability Theory
~ Main Modules ~
• System Concepts
• Multi-Attribute Choice
• Linear Programming
• MP Extensions
• Decision Analysis
• Expected Utility
• Game Theory
• Discrete Simulation
• System Dynamics
• Behavioral Factors
• Mathematical Duality
~ Review Modules ~
• Strategic Management
• Probability Theory
• Cost Concepts
• Time Value of Money
~ Miscellanea ~
• Book Reviews
Info @ DecMod
Special Temporary Module: UPR ADMI 4006
>>> UPR - Trabajo Final ADMI 4006 <<<
Decision Modeling is under construction.
Decision Modeling started out on 20 August 2001 as a compilation of lecture notes for a management science course. The original site was hosted by MSN Groups. When MSN closed their service, a new DM site was begun at Google Sites. Unfortunately, the Google service is somewhat restrictive in terms of what developers can do with their sites. So DM migrated to Yola, which is light-years ahead of just about every other Web hosting service. Decision Modeling is now being rewritten and expanded within the DiegoAzeta.org cluster of personal education websites.
DM is a labor of love, which means that development work usually takes on a lower-than-desired priority. Think molasses, or better yet, Heinz ketchup. But despair not, for DM shall overcome . . . eventually.
Thank you for your much-appreciated patience!
A broad selection of encyclopedia articles on decision-related topics
Covers algebra, calculus, equations & inequalities (including graphs), and matrix algebra
Software tools for game theory
Calculators and other math resources
Integrated knowledge base and computational engine
Lecture notes, exams and course videos from the entire MIT curriculum
Analytics, a digital magazine published by the Institute for Operations Research and the Management Sciences
(INFORMS), provides readers with real-life examples of how data, modeling and mathematical analysis is used
to drive better business decisions and provide concrete competitive advantage.