ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE. School of Mathematical Sciences

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! ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE School of Mathematical Sciences New Revised COURSE: COS-MATH-312 Nonlinear Optimization 1.

9-20-11 Optional Course Designations: Yes No General Education Writing Intensive Honors Approval Request Date Approval Grant Date 2.

1 ! ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE School of Mathematical Sciences New Revised COURSE: COS-MATH-312 Nonlinear Optimization 1.0 Course designations and approvals: Required Course Approvals: Approval Approval Request Date Grant Date Academic Unit Curriculum Committee College Curriculum Committee Optional Course Designations: Yes No General Education Writing Intensive Honors Approval Request Date Approval Grant Date 2.0 Course information: Course Title: Nonlinear Optimization Credit Hours: 3 Prerequisite(s): COS-MATH-219 or -221, and COS-MATH-311 Co-requisite(s): None Course proposed by: School of Mathematical Sciences Effective date: Fall 2013 Contact Hours Maximum Students/section Classroom 3 35 Lab Workshop Other (specify) 2.1 Course conversion designation: (Please check which applies to this course) Semester Equivalent (SE) to: Semester Replacement (SR) to: New 2.2 Semester(s) offered: Fall Spring Summer Offered every other year only Other Page 1 of 5

2 2.3 Student requirements: Students required to take this course: (by program and year, as appropriate) None Students who might elect to take the course: Students majoring in Applied Statistics, Applied Mathematics, Computational Mathematics, Mathematics minors, and students in Industrial Engineering, Computer Science or Business 3.0 Goals of the course: (including rationale for the course, when appropriate) 3.1 To study the variety of optimization problems which can be formulated as linear and non-linear programming problems. 3.2 To analyze general optimization problems. 3.3 To analyze various optimization algorithms for applications. 3.4 To use software in solving optimization problems. 4.0 Course description: (as it will appear in the RIT Catalog, including pre- and co-requisites, semesters offered) COS-MATH-312 Nonlinear Optimization This course provides a study of the theory of optimization of non-linear functions of several variables with or without constraints. Applications of this theory in business, management, engineering, and the sciences are considered. Algorithms for practical applications will be analyzed and implemented. The course may require the use of specialized software to analyze problems. Students taking this course will be expected to complete applied projects and/or case studies. (COS-MATH-219 or -221, and COS-MATH-311 or permission of instructor) Class 3, Credit 3 (S) 5.0 Possible resources: (texts, references, computer packages, etc.) 5.1 Winston, W., Operations Research Applications and Algorithms, Duxbury Press, North Scituate, MA. 5.2 Hiller, F.S. and Liberman, G.J., Introduction to Operations Research, Holden-Day, San Francisco, CA. 5.3 Taha, H., Operations Research: An Introduction, Pearson-Prentice Hall, Upper Saddle River, NJ. 5.4 Bazaraa, M.S., and Shetty, C.M., Nonlinear Programming-Theory and Algorithms, Wiley, Hoboken, NJ. 5.5 McCormick, G.P., Nonlinear Programming: Theory and Applications, Wiley, Hoboken, NJ. 5.6 Software: Mathematica, Wolfram Research, Champaign, IL. 6.0 Topics: (outline) Topics with an asterisk(*) are at the instructor s discretion, as time permits 6.1 Integer Programming Branch and bound methods Page 2 of 5

3 6.1.2 Implicit enumeration Cutting plane methods Applications 6.2 Nonlinear Optimization Unconstrained optimization Search algorithms Constrained optimization Lagrange multipliers Kuhn-Tucker theory Gradient methods 6.3 Dynamic Programming Examples Backward recursion 7.0 Intended learning outcomes and associated assessment methods of those outcomes: Assessment Methods Learning Outcomes 7.1 Formulate optimization problems 7.2 Explain methods of optimization of linear and non-linear functions of several variables 7.3 Analyze optimization algorithms 7.4 Write programs or use software to implement the algorithms 8.0 Program goals supported by this course: 8.1 To develop an understanding of the mathematical framework that supports engineering, science, and mathematics. 8.2 To develop critical and analytical thinking. 8.3 To develop an appropriate level of mathematical literacy and competency. 8.4 To provide an acquaintance with mathematical notation used to express physical and natural laws. Page 3 of 5

4 9.0 General education learning outcomes and/or goals supported by this course: Assessment Methods General Education Learning Outcomes 9.1 Communication Express themselves effectively in common college-level written forms using standard American English Revise and improve written and visual content Express themselves effectively in presentations, either in spoken standard American English or sign language (American Sign Language or English-based Signing) Comprehend information accessed through reading and discussion 9.2 Intellectual Inquiry Review, assess, and draw conclusions about hypotheses and theories Analyze arguments, in relation to their premises, assumptions, contexts, and conclusions Construct logical and reasonable arguments that include anticipation of counterarguments Use relevant evidence gathered through accepted scholarly methods and properly acknowledge sources of information 9.3 Ethical, Social and Global Awareness Analyze similarities and differences in human experiences and consequent perspectives Examine connections among the world s populations Identify contemporary ethical questions and relevant stakeholder positions 9.4 Scientific, Mathematical and Technological Literacy Explain basic principles and concepts of one of the natural sciences Apply methods of scientific inquiry and problem solving to contemporary issues Comprehend and evaluate mathematical and statistical information Perform college-level mathematical operations on quantitative data Describe the potential and the limitations of technology Use appropriate technology to achieve desired outcomes Page 4 of 5

5 Assessment Methods General Education Learning Outcomes 9.5 Creativity, Innovation and Artistic Literacy Demonstrate creative/innovative approaches to coursebased assignments or projects Interpret and evaluate artistic expression considering the cultural context in which it was created 10.0 Other relevant information: (such as special classroom, studio, or lab needs, special scheduling, media requirements, etc.) 10.1 Smart classroom 10.2 Optimization software: LINDO, Mathematica Page 5 of 5

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