Optimization Problems for All Levels

Brian J. Anderson; Robin S. Hissam; Joseph A. Shaeiwitz; Richard Turton

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Conference: 2011 ASEE Annual Conference & Exposition
Location: Vancouver, BC
Publication Date: June 26, 2011
Start Date: June 26, 2011
End Date: June 29, 2011
ISSN: 2153-5965
Conference Session: Focus on Entry Experiences in Chemical Engineering
Tagged Division: Chemical Engineering
Page Count: 14
Page Numbers: 22.1127.1 - 22.1127.14
DOI: 10.18260/1-2--18363
Permanent URL: https://peer.asee.org/18363
Download Count: 2154

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Paper Authors

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Brian J. Anderson West Virginia University

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Brian J. Anderson is the Verl Purdy Faculty Fellow and an Assistant Professor in the Department of Chemical Engineering at West Virginia University. Dr. Anderson’s research experience includes sustainable energy and development, economic modeling of energy systems, and geothermal energy development as well as molecular and reservoir modeling.

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Robin S. Hissam West Virginia University

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Robin Hissam received her Bachelor’s and Master’s degrees in Materials Science and Engineering from Virginia Tech. The focus of her research as both an undergraduate and graduate at Virginia Tech was polymer physics, in particular, the crystallization of polymers. Robin joined the Materials Science and Engineering department at the University of Delaware as a Ph.D. candidate in 2001, where her research under Dr. Kristi Kiick involved the design, synthesis and characterization of protein polymers for applications in toxin inhibition. Graduating in 2006, Robin joined the group of Dr. Kimberly Woodhouse in Chemical Engineering and Applied Chemistry at the University of Toronto for a two year postdoctoral fellowship. The research in Toronto looked at the possible application of elastin-based protein polymers for drug delivery vehicles. For her work in this area, Robin received a scholarship from the Advanced Regenerative Tissue Engineering Centre. At West Virginia University, Robin is continuing her work in production of protein polymers for application in tissue engineering, biomineralization, and biosensors.

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Joseph A. Shaeiwitz West Virginia University

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Joseph A. Shaeiwitz received his B.S. degree from the University of Delaware and his M.S. and Ph.D. degrees from Carnegie Mellon University. His professional interests are in design, design education, and outcomes assessment. Joe is a co-author of the text Analysis, Synthesis, and Design of Chemical Processes (3rd ed.), published by Prentice Hall in 2009.

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Richard Turton West Virginia University

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Richard Turton has taught Process Design at West Virginia University for the past 25 years and is co-author of the text "Analysis, Synthesis and Design of Chemical Processes" published by Pearson. His current research interests are in the area of dynamic simulation and control of advanced power generation systems and in engineering design education.

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Abstract

Optimization is often considered to be an advanced, highly mathematical, and sometimes an obscure discipline. Optimization problems that have been developed and are suitable for undergraduate engineering students at all levels will be presented. Two of these problems will be described in detail, and many others are available on the web (URL to be provided in final paper). The ability to solve “routine” optimization problems has been simplified by advances in computing power over the last generation. Design textbooks of the previous generation presented a sequence of optimization techniques aimed at minimizing the number of cases that had to be considered to reduce the search space for the optimization. While it is possible to perform optimization calculations using solver algorithms within software like Excel, the goal of the problems discussed here is to force students to understand the features that lead to an optimum. Therefore, these problem statements are posed to require the presentation of results in a way that forces students to understand the trends for the different terms comprising the objective function and how they combine to yield an optimum. The result is an understanding of the trade-off necessary for an optimum to exist. Three levels of optimization problems are available, and they are summarized in Table 1. The ones highlighted in italics are discussed in this paper, and the others are available on the web. The numbers in parenthesis indicate the number of different versions available. All of these have been used successfully in a freshman class aimed at developing computing skills appropriate for an undergraduate chemical engineering student along with problem-solving skills. Most of these problems would also be suitable, with appropriate changes consistent with the students’ more advanced subject material understanding, for assignments or projects in unit operations classes or as problem assignments for the portion of a design class where optimization is taught. Table 1: Available Optimization Problems Single Variable Multi-variable ProjectsPipe diameter (2) Absorber Generic chemical process (2)Reactor/preheater (2) Batch reactor/preheater Geothermal energy (2)Reflux ratio Staged compressors Fuel production from biomass (4)

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Anderson, B. J., & Hissam, R. S., & Shaeiwitz, J. A., & Turton, R. (2011, June), Optimization Problems for All Levels Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. 10.18260/1-2--18363

TY  - CPAPER
AB  -     Optimization is often considered to be an advanced, highly mathematical, and sometimes an obscure discipline. Optimization problems that have been developed and are suitable for undergraduate engineering students at all levels will be presented. Two of these problems will be described in detail, and many others are available on the web (URL to be provided in final paper).     The ability to solve “routine” optimization problems has been simplified by advances in computing power over the last generation. Design textbooks of the previous generation presented a sequence of optimization techniques aimed at minimizing the number of cases that had to be considered to reduce the search space for the optimization. While it is possible to perform optimization calculations using solver algorithms within software like Excel, the goal of the problems discussed here is to force students to understand the features that lead to an optimum. Therefore, these problem statements are posed to require the presentation of results in a way that forces students to understand the trends for the different terms comprising the objective function and how they combine to yield an optimum. The result is an understanding of the trade-off necessary for an optimum to exist.      Three levels of optimization problems are available, and they are summarized in Table 1. The ones highlighted in italics are discussed in this paper, and the others are available on the web. The numbers in parenthesis indicate the number of different versions available. All of these have been used successfully in a freshman class aimed at developing computing skills appropriate for an undergraduate chemical engineering student along with problem-solving skills. Most of these problems would also be suitable, with appropriate changes consistent with the students’ more advanced subject material understanding, for assignments or projects in unit operations classes or as problem assignments for the portion of a design class where optimization is taught.                            Table 1: Available Optimization Problems        Single Variable               Multi-variable                      ProjectsPipe diameter (2)               Absorber                    Generic chemical process (2)Reactor/preheater (2)           Batch reactor/preheater     Geothermal energy (2)Reflux ratio                    Staged compressors          Fuel production from biomass (4)
AU  - Brian J. Anderson
AU  - Robin S. Hissam
AU  - Joseph A. Shaeiwitz
AU  - Richard Turton
CY  - Vancouver, BC
DA  - 2011/06/26
PB  - ASEE Conferences
TI  - Optimization Problems for All Levels
UR  - https://peer.asee.org/18363
DO  - 10.18260/1-2--18363
ER  -