Bezmaksas piegāde pasūtījumiem virs 29€

  • check 10+ miljoni grāmatu
  • check Jaunumi katru dienu
  • check Vairāk nekā 1 miljons klientu mums uzticas
  • check Labas cenas un atlaides
  • check Piegāde visā Eiropā

BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems - Urmila Diwekar,Amy David

angļu valoda
2015-03-06
63,51 € 84,68 €

-25% ar kodu BOOKS

Piegādātāja noliktavā

Piegāde 12-18 darba dienu laikā

30 dienu atgriešanas politika

This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistica ... Pilns apraksts

Jums varētu patikt arī

Aprašymas

This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.

Vairāk informācijas

Autors Urmila Diwekar, Amy David
Izdevējs Springer New York
Series SpringerBriefs in Optimization
Izlaides gads 2015
Vāka tips Mīkstais vāks
EAN 9781493922819
Rakstiet savu atsauksmi
Jūs vērtējat: BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems
Jūsu novērtējums:

Goodreads atsauksmes

63,51 € 84,68 €