Credits: 3


Prerequisite: ENME271; or MATH206.
Restriction: Permission of ENGR-Mechanical Engineering department; and junior or senior standing.
Introduction to the formal process of design optimization, including analytical and computational methods. Step by step design optimization techniques. Design optimization concepts, necessary and sufficient optimality conditions and solution techniques. Solution evaluation and tradeoff exploration.

Semesters Offered

Spring 2018, Spring 2021, Spring 2022, Spring 2024

Learning Objectives

The course gives an introductory overview of “single-objective” design optimization concepts, models and techniques. Students will learn how to do the following:

  1. Formulate a formal design optimization problem
  2. Solve the problem
  3. Assess and validate solution results,
  4. Work as a team, communicate and report effectively the outcome of their project activity


Topics Covered

  • Introduction, examples and concepts
  • Optimality conditions
  • Single objective: unconstrained methods
  • Single objective: constrained methods
  • Mid-term exam, quizzes, project meetings, presentations


Learning Outcomes

  • an ability to apply knowledge of mathematics, science, and engineering
  • an ability to design and conduct experiments, as well as to analyze and interpret data
  • an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
  • an ability to identify, formulate, and solve engineering problems
  • an ability to communicate effectively
  • a knowledge of contemporary issues
  • an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
  • an ability to work professionally in both thermal and mechanical systems areas

Additional Course Information


Azarm, Shapour


  • Introduction to Optimum Design, Arora, J.S., 4th Edition, 2017, Academic Press (ISBN: 97801238008065). 
  • (Recommended:) An Engineer’s Guide to Matlab, Magrab et al., 3rd Edition, 2011, Prentice Hall (ISBN: 9780131991101).

Class/Laboratory Schedule 

  • Two 75-minute lecture sessions per week