Using Nonlinear Programming to Optimize the Fiber Packing Density of Optical Fiber Cables- A Short Problem-Based Learning Course

Kenneth W. Jackson; Gregory L. Wiles

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Conference: 2013 ASEE Annual Conference & Exposition
Location: Atlanta, Georgia
Publication Date: June 23, 2013
Start Date: June 23, 2013
End Date: June 26, 2013
ISSN: 2153-5965
Conference Session: Software Applications in ET Programs
Tagged Division: Engineering Technology
Page Count: 10
Page Numbers: 23.1331.1 - 23.1331.10
DOI: 10.18260/1-2--22716
Permanent URL: https://peer.asee.org/22716
Download Count: 374

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Paper Authors

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Kenneth W. Jackson Southern Polytechnic State University

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Kenneth W. Jackson, Ph.D. – P.E.

Dr. Ken Jackson received his Ph.D. in Mechanical Engineering from the Georgia Institute of Technology. He also holds an M.S.M.E and a M.S. I.E. from Georgia Tech and a B.S.M.E from Auburn University. Before joining SPSU he worked for 15 years at the Bell Laboratories as a Consulting and Distinguished Member of Technical Staff. At Bell Labs Dr. Jackson worked on the design, development and commercialization of fiber optic products for telecommunication systems and their associated manufacturing processes. Before joining Bell Laboratories he also worked for the Western Electric Company in defense activities, manufacturing and product engineering. Dr. Jackson's technical interests include statistical computing, applying innovative methods to improve industrial systems’ performance and the development and application of system-structured design and development tools to reduce the cost and increase the quality of new products. Dr. Jackson has authored 17 patents and has published/presented 23 technical papers. He is a Registered Professional Engineer in Georgia, a member of the American Society for Quality and the ASME.

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Gregory L. Wiles P.E. Southern Polytechnic State University

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An assistant professor of industrial engineering technology at Southern Polytechnic State University, a four-year technical university in Georgia. He has a BS degree in Industrial Engineering at the University of Tennessee, an MS degree in Industrial & Systems Engineering at the Georgia Institute of Technology, and currently working on his PhD. Prior to teaching, he worked for Lockheed Martin, Union Carbide, nVision Global, Oracle, and Georgia Tech in various engineering roles from research, to technical sales, to division management.

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Abstract

ETD IT/IET Interest Group Optimizing Optical Fiber Cable Design Using Nonlinear Programming-A Special Problems CourseThis paper describes the design and delivery of a special problems course in which we use thecase method to teach students nonlinear programming and provide them experience in attackingan ill-structured, real-world problem. Traditionally, engineering, engineering technology andbusiness students who take operations research are only taught linear programming foroptimizing a linear objective function subject to linear constraints. For many applications inengineering, operations, business and economics the linearity assumption does not accuratelydescribe either the objective or the constraints. Thus, nonlinear programming (NLP) with integeror mixed decision variables has become an important tool for optimizing various engineering andbusiness operations and physical designs. In addition, nonlinear optimization provides a moreintuitive understanding of how an optimization algorithm works through the analogy to hillclimbing. The simplex algorithm used for linear programming is non-intuitive and it can beconceptually difficult for many students to understand. The availability of affordable and user-friendly software now makes it feasible to introduce students to NLP as an extension to theiroperations research studies.The basic problem involves maximizing the number of optical fibers that can be placed into acable core having a nominally circular cross-section. Maximizing the fiber packing density formany applications minimizes the installed cost per fiber for the customer. Significantly, tofacilitate mass splicing the fibers are pre-packaged into rectangular ribbon arrays comprisingvariable fiber counts before placement into the cylindrical cable core during the manufacturingprocess. Students use integer NLP to explore the optimal design space for cables under a varietyof constraints. The formulation requires linear and nonlinear constraints to describe the addedloss, stability and symmetry criteria for the ribbon stack. Similar constraints may also existbetween the global and local rectangular geometry of the ribbon stack and the circular cross-section of the cable core. Students learn to use the LINGO software package to analyzeexemplary cable design configurations and to explore the design space. We evolve the problemcomplexity to allow the students to discover new constraints, practical considerations and how toidentify and remove infeasibilities that arise as the nature of the problem expands. Students writean engineering report, present and discuss their results. The course is team-taught by twoprofessors acting as supervisors in order to simulate communications in a typical workenvironment. The course provides students with experiential learning involving ill-structuredproblems that the National Academy of Engineering has identified as critical for competitivenessin the 21st century. It also teaches students NLP and facilitates their conceptual understanding ofoptimization algorithms.

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Jackson, K. W., & Wiles, G. L. (2013, June), Using Nonlinear Programming to Optimize the Fiber Packing Density of Optical Fiber Cables- A Short Problem-Based Learning Course Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22716

TY - CPAPER
AB - ETD IT/IET Interest Group Optimizing Optical Fiber Cable Design Using Nonlinear Programming-A Special Problems CourseThis paper describes the design and delivery of a special problems course in which we use thecase method to teach students nonlinear programming and provide them experience in attackingan ill-structured, real-world problem. Traditionally, engineering, engineering technology andbusiness students who take operations research are only taught linear programming foroptimizing a linear objective function subject to linear constraints. For many applications inengineering, operations, business and economics the linearity assumption does not accuratelydescribe either the objective or the constraints. Thus, nonlinear programming (NLP) with integeror mixed decision variables has become an important tool for optimizing various engineering andbusiness operations and physical designs. In addition, nonlinear optimization provides a moreintuitive understanding of how an optimization algorithm works through the analogy to hillclimbing. The simplex algorithm used for linear programming is non-intuitive and it can beconceptually difficult for many students to understand. The availability of affordable and user-friendly software now makes it feasible to introduce students to NLP as an extension to theiroperations research studies.The basic problem involves maximizing the number of optical fibers that can be placed into acable core having a nominally circular cross-section. Maximizing the fiber packing density formany applications minimizes the installed cost per fiber for the customer. Significantly, tofacilitate mass splicing the fibers are pre-packaged into rectangular ribbon arrays comprisingvariable fiber counts before placement into the cylindrical cable core during the manufacturingprocess. Students use integer NLP to explore the optimal design space for cables under a varietyof constraints. The formulation requires linear and nonlinear constraints to describe the addedloss, stability and symmetry criteria for the ribbon stack. Similar constraints may also existbetween the global and local rectangular geometry of the ribbon stack and the circular cross-section of the cable core. Students learn to use the LINGO software package to analyzeexemplary cable design configurations and to explore the design space. We evolve the problemcomplexity to allow the students to discover new constraints, practical considerations and how toidentify and remove infeasibilities that arise as the nature of the problem expands. Students writean engineering report, present and discuss their results. The course is team-taught by twoprofessors acting as supervisors in order to simulate communications in a typical workenvironment. The course provides students with experiential learning involving ill-structuredproblems that the National Academy of Engineering has identified as critical for competitivenessin the 21st century. It also teaches students NLP and facilitates their conceptual understanding ofoptimization algorithms.
AU - Kenneth W. Jackson
AU - Gregory L. Wiles P.E.
CY - Atlanta, Georgia
DA - 2013/06/23
PB - ASEE Conferences
TI - Using Nonlinear Programming to Optimize the Fiber Packing Density of Optical Fiber Cables- A Short Problem-Based Learning Course
UR - https://peer.asee.org/22716
DO - 10.18260/1-2--22716
ER -