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You searched for +publisher:"Clemson University" +contributor:("Margaret M Wiecek"). Showing records 1 – 4 of 4 total matches.

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Clemson University

1. Murdaugh, Amy. Modeling and Optimization of Self-Healing Polymers.

Degree: MS, Mathematical Sciences, 2020, Clemson University

  Continuous interests in developing self-healable polymers are driven by the desire to extend life spans of existing functional materials. Combining mathematical modeling and optimization… (more)

Subjects/Keywords: numerical modeling; optimization; self-healable polymers; thin-film equation

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APA (6th Edition):

Murdaugh, A. (2020). Modeling and Optimization of Self-Healing Polymers. (Masters Thesis). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_theses/3285

Chicago Manual of Style (16th Edition):

Murdaugh, Amy. “Modeling and Optimization of Self-Healing Polymers.” 2020. Masters Thesis, Clemson University. Accessed August 14, 2020. https://tigerprints.clemson.edu/all_theses/3285.

MLA Handbook (7th Edition):

Murdaugh, Amy. “Modeling and Optimization of Self-Healing Polymers.” 2020. Web. 14 Aug 2020.

Vancouver:

Murdaugh A. Modeling and Optimization of Self-Healing Polymers. [Internet] [Masters thesis]. Clemson University; 2020. [cited 2020 Aug 14]. Available from: https://tigerprints.clemson.edu/all_theses/3285.

Council of Science Editors:

Murdaugh A. Modeling and Optimization of Self-Healing Polymers. [Masters Thesis]. Clemson University; 2020. Available from: https://tigerprints.clemson.edu/all_theses/3285


Clemson University

2. Hunt, Brian J. Multiobjective Programming with Convex Cones: Methodology and Applications.

Degree: PhD, Mathematical Science, 2004, Clemson University

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APA (6th Edition):

Hunt, B. J. (2004). Multiobjective Programming with Convex Cones: Methodology and Applications. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/arv_dissertations/635

Chicago Manual of Style (16th Edition):

Hunt, Brian J. “Multiobjective Programming with Convex Cones: Methodology and Applications.” 2004. Doctoral Dissertation, Clemson University. Accessed August 14, 2020. https://tigerprints.clemson.edu/arv_dissertations/635.

MLA Handbook (7th Edition):

Hunt, Brian J. “Multiobjective Programming with Convex Cones: Methodology and Applications.” 2004. Web. 14 Aug 2020.

Vancouver:

Hunt BJ. Multiobjective Programming with Convex Cones: Methodology and Applications. [Internet] [Doctoral dissertation]. Clemson University; 2004. [cited 2020 Aug 14]. Available from: https://tigerprints.clemson.edu/arv_dissertations/635.

Council of Science Editors:

Hunt BJ. Multiobjective Programming with Convex Cones: Methodology and Applications. [Doctoral Dissertation]. Clemson University; 2004. Available from: https://tigerprints.clemson.edu/arv_dissertations/635


Clemson University

3. Engau, Alexander. Exploring Epsilon-Efficiency in Multiobjective Programming.

Degree: MS, Mathematical Science, 2004, Clemson University

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Engau, A. (2004). Exploring Epsilon-Efficiency in Multiobjective Programming. (Masters Thesis). Clemson University. Retrieved from https://tigerprints.clemson.edu/arv_theses/2425

Chicago Manual of Style (16th Edition):

Engau, Alexander. “Exploring Epsilon-Efficiency in Multiobjective Programming.” 2004. Masters Thesis, Clemson University. Accessed August 14, 2020. https://tigerprints.clemson.edu/arv_theses/2425.

MLA Handbook (7th Edition):

Engau, Alexander. “Exploring Epsilon-Efficiency in Multiobjective Programming.” 2004. Web. 14 Aug 2020.

Vancouver:

Engau A. Exploring Epsilon-Efficiency in Multiobjective Programming. [Internet] [Masters thesis]. Clemson University; 2004. [cited 2020 Aug 14]. Available from: https://tigerprints.clemson.edu/arv_theses/2425.

Council of Science Editors:

Engau A. Exploring Epsilon-Efficiency in Multiobjective Programming. [Masters Thesis]. Clemson University; 2004. Available from: https://tigerprints.clemson.edu/arv_theses/2425

4. Adelgren, Nathan. Solution Techniques for Classes of Biobjective and Parametric Programs.

Degree: PhD, Mathematical Science, 2016, Clemson University

 Mathematical optimization, or mathematical programming, has been studied for several decades. Researchers are constantly searching for optimization techniques which allow one to de-termine the ideal… (more)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Adelgren, N. (2016). Solution Techniques for Classes of Biobjective and Parametric Programs. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1754

Chicago Manual of Style (16th Edition):

Adelgren, Nathan. “Solution Techniques for Classes of Biobjective and Parametric Programs.” 2016. Doctoral Dissertation, Clemson University. Accessed August 14, 2020. https://tigerprints.clemson.edu/all_dissertations/1754.

MLA Handbook (7th Edition):

Adelgren, Nathan. “Solution Techniques for Classes of Biobjective and Parametric Programs.” 2016. Web. 14 Aug 2020.

Vancouver:

Adelgren N. Solution Techniques for Classes of Biobjective and Parametric Programs. [Internet] [Doctoral dissertation]. Clemson University; 2016. [cited 2020 Aug 14]. Available from: https://tigerprints.clemson.edu/all_dissertations/1754.

Council of Science Editors:

Adelgren N. Solution Techniques for Classes of Biobjective and Parametric Programs. [Doctoral Dissertation]. Clemson University; 2016. Available from: https://tigerprints.clemson.edu/all_dissertations/1754

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