Making Better Decisions: Tools for Decisions with Multiple Objectives (Self Study)
Course Type:
Self Study
Course Number:
EL595Language:
In this course, students learn to use a systematic process to organize information and analyze decisions with multiple objectives.
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Course Access
This Self Study course is designed to be taken at your convenience and on your own schedule. You have 365 days from the time of purchase to finish the course.
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In this course, students learn to use a systematic process to organize information and analyze decisions with multiple objectives. Participants will learn to gather and structure relevant information, develop models of the decision-maker’s preferences, use those models to identify the best alternative, and evaluate the sensitivity of the result.
By participating in this course, you will learn how to successfully:
- Organize relevant information to structure a decision with multiple alternatives and multiple objectives.
- Formulate appropriate utility functions that model the decision-maker's preferences in a decision with multiple alternatives and multiple objectives.
- Evaluate alternatives using appropriate utility functions and recommend the best alternative in a decision with multiple alternatives and multiple objectives.
- Measure and visualize the sensitivity of the alternatives' relative value in a decision with multiple alternatives and multiple objectives.
Who should attend?
This course is designed for:
- Engineers who make decisions during product and system design and when managing projects and teams.
- Anyone who wants to learn a systematic decision-making process.
Course Materials (included in purchase of course)
- Digital course notes via ASME’s Learning Hub
- Downloadable resources
A Certificate of Completion will be issued to registrants who successfully complete the course by achieving a passing score of 75% or higher on the final exam.
Module 0: Course Introduction
Module 1: Structuring a Decision
Module 2: Defining Attribute Utility Functions
Module 3: Constructing a Multi-attribute Utility Function
Module 4: Identifying the Best Alternative
Module 5: Sensitivity Analysis
Jeffrey W. Herrmann, Ph.D.
Professor, Department of Mechanical Engineering
Jeffrey W. Herrmann, Ph.D., holds the St. Abbo of Fleury Endowed Chair in Engineering and serves as a professor in the Department of Mechanical Engineering within the College of Engineering, Physics, and Computing at the Catholic University of America.
More Information
Self Study
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