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Algorithms for multi-objective optim...

University of California, Merced.

Algorithms for multi-objective optimization of dynamical systems.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Algorithms for multi-objective optimization of dynamical systems./
作者:	Naranjani, Yousef.
面頁冊數:	1 online resource (131 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.
Contained By:	Dissertation Abstracts International78-04B(E).
標題:	Mechanical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369188981

Algorithms for multi-objective optimization of dynamical systems.
Naranjani, Yousef.

Algorithms for multi-objective optimization of dynamical systems. - 1 online resource (131 pages)

Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Multi-Objective Optimization Problems (MOPs) deal with optimizing several objectives simultaneously and have diverse applications in engineering, economics, logistics, etc. The methods for solving MOPs can generally be classified into stochastic and deterministic approaches. Deterministic approaches are capable of finding the global solution even though they are computationally burdensome. Stochastic methods, on the other hand, can save on computations significantly, although they do not guarantee to find the global solution.

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

Mode of access: World Wide Web

ISBN: 9781369188981Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Algorithms for multi-objective optimization of dynamical systems.
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099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Naranjani, Yousef. $3 1180314
245 1 0 $a Algorithms for multi-objective optimization of dynamical systems.
264 0 $c 2016
300 $a 1 online resource (131 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
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500 $a Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.
500 $a Adviser: Jian-Qiao Sun.
502 $a Thesis (Ph.D.) $c University of California, Merced $d 2016.
504 $a Includes bibliographical references
520 $a Multi-Objective Optimization Problems (MOPs) deal with optimizing several objectives simultaneously and have diverse applications in engineering, economics, logistics, etc. The methods for solving MOPs can generally be classified into stochastic and deterministic approaches. Deterministic approaches are capable of finding the global solution even though they are computationally burdensome. Stochastic methods, on the other hand, can save on computations significantly, although they do not guarantee to find the global solution.
520 $a In engineering applications, MOPs can become nonlinear, multi-modal, high dimensional, and have complex structured solutions that makes them more challenging.
520 $a This theses follows two major goals. Firstly, it presents new methods and algorithms for solving engineering MOPs by hybridizing the existing methods and comparing their effectiveness by using benchmark problems. The hybrid method combines an evolutionary algorithm with a cell mapping method in order to reduce the computational time while maintaining the quality of the solution. Implementation details on parallel CPU/GPU programming of such methods are discussed as well. The second goal of this thesis is to introduce new applications of MOPs in different areas of engineering such as control design, path planning, fractional systems and airfoil design.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Systems science. $3 1148479
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0790
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Merced. $b Mechanical Engineering. $3 1180313
773 0 $t Dissertation Abstracts International $g 78-04B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10164406 $z click for full text (PQDT)

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