國立虎尾科技大學 |

Multi-Objective Optimization Under Uncertainty.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Multi-Objective Optimization Under Uncertainty./
作者:	Sigler, Devon Peter.
面頁冊數:	1 online resource (172 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
Contained By:	Dissertation Abstracts International79-01B(E).
標題:	Operations research. -
電子資源:	click for full text (PQDT)
ISBN:	9780355139204

Multi-Objective Optimization Under Uncertainty.
Sigler, Devon Peter.

Multi-Objective Optimization Under Uncertainty. - 1 online resource (172 pages)

Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

In this dissertation we investigate multi-objective optimization problems subject to uncertainty. In the first part, as an application and synthesis of existing theory, we consider the problem of optimally charging an electric vehicle with respect to uncertainty in future electricity prices and future driving patterns. To provide further advancement of theory and methodology for such problems, in the second part of this thesis we focus on the more specific case of multi-objective problems where the objective function values are subject to uncertainty. The theory presented provides new notions of Pareto optimality for multi-objective optimization problems under uncertainty, and provides scalarization and existence results for the new Pareto optimal solution classes presented. Theory from functional analysis and vector optimization is then utilized to analyze the new solution classes we have presented. Finally, we generalize the minimax-regret criterion to multi-objective optimization problems under uncertainty, and use the results obtained from functional analysis and vector optimization to analyze these solutions' relationship with the new notions of Pareto optimality we have defined.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355139204Subjects--Topical Terms:

573517
Operations research.
Index Terms--Genre/Form:

554714
Electronic books.

Multi-Objective Optimization Under Uncertainty.
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300 $a 1 online resource (172 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
500 $a Advisers: Stephen Billups; Jan Mandel.
502 $a Thesis (Ph.D.) $c University of Colorado at Denver $d 2017.
504 $a Includes bibliographical references
520 $a In this dissertation we investigate multi-objective optimization problems subject to uncertainty. In the first part, as an application and synthesis of existing theory, we consider the problem of optimally charging an electric vehicle with respect to uncertainty in future electricity prices and future driving patterns. To provide further advancement of theory and methodology for such problems, in the second part of this thesis we focus on the more specific case of multi-objective problems where the objective function values are subject to uncertainty. The theory presented provides new notions of Pareto optimality for multi-objective optimization problems under uncertainty, and provides scalarization and existence results for the new Pareto optimal solution classes presented. Theory from functional analysis and vector optimization is then utilized to analyze the new solution classes we have presented. Finally, we generalize the minimax-regret criterion to multi-objective optimization problems under uncertainty, and use the results obtained from functional analysis and vector optimization to analyze these solutions' relationship with the new notions of Pareto optimality we have defined.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Operations research. $3 573517
655 7 $a Electronic books. $2 local $3 554714
690 $a 0796
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Colorado at Denver. $b Applied Mathematics. $3 1182264
773 0 $t Dissertation Abstracts International $g 79-01B(E).
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