Nonsmooth Optimization in Honor of the 60th Birthday of Adil M. Bagirov
Napsu Karmitsa, "Nonsmooth Optimization in Honor of the 60th Birthday of Adil M. Bagirov"
English | ISBN: 3039438352 | 2020 | 116 pages | PDF | 2 MB
The aim of this book was to collect the most recent methods developed for NSO and its practical applications. The book contains seven papers: The first is the foreword by the Guest Editors giving a brief review of NSO and its real-life applications and acknowledging the outstanding contributions of Professor Adil Bagirov to both the theoretical and practical aspects of NSO. The second paper introduces a new and very efficient algorithm for solving uncertain unit-commitment (UC) problems. The third paper proposes a new nonsmooth version of the generalized damped Gauss-Newton method for solving nonlinear complementarity problems. In the fourth paper, the abs-linear representation of piecewise linear functions is extended to yield simultaneously their DC decomposition as well as the pair of generalized gradients. The fifth paper presents the use of biased-randomized algorithms as an effective methodology to cope with NP-hard and nonsmooth optimization problems in many practical applications. In the sixth paper, a problem concerning the scheduling of nuclear waste disposal is modeled as a nonsmooth multiobjective mixed-integer nonlinear optimization problem, and a novel method using the two-slope parameterized achievement scalarizing functions is introduced. Finally, the last paper considers binary classification of a multiple instance learning problem and formulates the learning problem as a nonconvex nonsmooth unconstrained optimization problem with a DC objective function.
Read more
Links are Interchangeable - Single Extraction
Napsu Karmitsa, "Nonsmooth Optimization in Honor of the 60th Birthday of Adil M. Bagirov"
English | ISBN: 3039438352 | 2020 | 116 pages | PDF | 2 MB
The aim of this book was to collect the most recent methods developed for NSO and its practical applications. The book contains seven papers: The first is the foreword by the Guest Editors giving a brief review of NSO and its real-life applications and acknowledging the outstanding contributions of Professor Adil Bagirov to both the theoretical and practical aspects of NSO. The second paper introduces a new and very efficient algorithm for solving uncertain unit-commitment (UC) problems. The third paper proposes a new nonsmooth version of the generalized damped Gauss-Newton method for solving nonlinear complementarity problems. In the fourth paper, the abs-linear representation of piecewise linear functions is extended to yield simultaneously their DC decomposition as well as the pair of generalized gradients. The fifth paper presents the use of biased-randomized algorithms as an effective methodology to cope with NP-hard and nonsmooth optimization problems in many practical applications. In the sixth paper, a problem concerning the scheduling of nuclear waste disposal is modeled as a nonsmooth multiobjective mixed-integer nonlinear optimization problem, and a novel method using the two-slope parameterized achievement scalarizing functions is introduced. Finally, the last paper considers binary classification of a multiple instance learning problem and formulates the learning problem as a nonconvex nonsmooth unconstrained optimization problem with a DC objective function.
Read more
Код:
[b]AusFile[/b]
https://ausfile.com/s5tdlebz1r8t/6tt25.7z.html
Rapidgator
https://rg.to/file/4878fddd7ff49474896cd4bf0512863a/6tt25.7z.html
TakeFile
https://takefile.link/eq28mv6274sv/6tt25.7z.html
[b]Fileaxa[/b]
https://fileaxa.com/3nsrn5gzpbsr/6tt25.7z
Fikper
https://fikper.com/I2ItzcOCUP/6tt25.7z.html
