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Introducing Single Criterion Optimization Methods Into Mechanics Classes

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Conference

2002 Annual Conference

Location

Montreal, Canada

Publication Date

June 16, 2002

Start Date

June 16, 2002

End Date

June 19, 2002

ISSN

2153-5965

Conference Session

Integrating Math and Engineering

Page Count

15

Page Numbers

7.749.1 - 7.749.15

DOI

10.18260/1-2--10583

Permanent URL

https://peer.asee.org/10583

Download Count

87

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Paper Authors

author page

William Szaroletta

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Abstract

Single criterion optimization problems are shown to be readily taught and understood at lower division course levels using algebra/calculus, exhaustive numerical searches, and solver-type tools in standard spreadsheet packages. Genetic algorithms provide another suitable numerical technique that is relatively easily understood by students in high-level form, directly applicable to the single criterion class of optimization problems and very helpful to the multiple criteria class of optimization problems. This paper describes the methods of lower-division mechanics classroom introduction of optimization methods including algebra/calculus, spreadsheet solver, exhaustive search, and genetic algorithms. A classical solid mechanics problem utilizing the simply supported beam with a central load is used as the baseline in this paper for presenting the optimization methods introduced. Several other more complex problems are described. Multiple criteria optimization problems, which can quickly exceed the capability of typical spreadsheet solver tools, require students to utilize the multiple criteria optimization capability of genetic algorithms software. A possible framework that would support both single criterion and multiple criteria optimization methods, based on using genetic algorithms software, is presented that could allow these powerful methods to be introduced and successfully utilized earlier in the student’s college experience.

Szaroletta, W. (2002, June), Introducing Single Criterion Optimization Methods Into Mechanics Classes Paper presented at 2002 Annual Conference, Montreal, Canada. 10.18260/1-2--10583

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