Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Robust optimization" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-5 z 5
    Tytuł:
    Robust Optimization Model for Spatial Land-Use Allocation Problem in Jatinangor Subdistrict, Indonesia
    Autorzy:
    Romhadhoni, Putri
    Chaerani, Diah
    Ruchjana, Budi Nurani
    Powiązania:
    https://bibliotekanauki.pl/articles/1031447.pdf
    Data publikacji:
    2020
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Jatinangor Subdistrict
    Land-use Allocation
    Robust Optimization
    Spatial Optimization
    Opis:
    Land-use planning become an important thing to do because some types of land-use can have an impact to environment and life quality. Land-use planning is generally an activity that involves the allocation of activities in a particular land. Spatial Optimization can be applied in land-use planning activity. This research aims to make Robust Optimization model for spatial land-use allocation problem in Jatinangor. Optimization model for land-use allocation problem aims to determine the percentage of land-use changes that can maximize comprehensive index and compactness index. In land-use planning, there are several uncertainty factors. Therefore, it’s needed an approach that can handle uncertainty factor, the approach used in this research is Robust Optimization. The result of Robust Optimization Model for land-use allocation problem which is solved by the box uncertainty set approach is a computationally tractable optimization model.
    Źródło:
    World Scientific News; 2020, 142; 44-59
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    • odwiedzone
    Tytuł:
    Adjustable Robust Counterpart Optimization Model for Maximum Flow Problems with Box Uncertainty
    Autorzy:
    Agustini, Rahmah Arie
    Chaerani, Diah
    Hertini, Elis
    Powiązania:
    https://bibliotekanauki.pl/articles/1031851.pdf
    Data publikacji:
    2020
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Adjustable Robust Counterpart
    Linear Programming
    Maximum flow problem
    Robust Optimization
    Opis:
    The maximum flow problem is an optimization problem that aims to find the maximum flow value on a network. This problem can be solved by using Linear Programming. The obstacle that is often faced in determining the maximum flow is the magnitude of the capacity of each side of the network can often be changed due to certain factors. Therefore, we need one of the optimization fields that can calculate the uncertainty factor. The field of optimization carried out to overcome these uncertainties is Robust Optimization. This paper discusses the Optimization model for the maximum flow problem by calculating the uncertainties on parameters and adjustable variables using the Adjustable Robust Counterpart (ARC) Optimization model. In this ARC Optimization model it is assumed that there are indeterminate parameters in the form of side capacity in a network and an uncertain decision variable that is the amount of flow from the destination point (sink) to the source point (source). Calculation results from numerical simulations show that the ARC Optimization model provides the maximum number of flows in a network with a set of box uncertainty. Numerical simulations were obtained with Maple software.
    Źródło:
    World Scientific News; 2020, 141; 91-102
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Uncertain Semivariogram Model using Robust Optimization for Application of Lead Pollutant Data
    Autorzy:
    Azizah, Annisa
    Ruchjana, Budi Nurani
    Chaerani, Diah
    Powiązania:
    https://bibliotekanauki.pl/articles/1030126.pdf
    Data publikacji:
    2020
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Lead Pollutan
    Linear Programming
    Robust Optimization
    Semivariogram
    Software R
    Opis:
    Semivariogram is a half variance diagram of the difference between observations at the location s_i with another location that is as far as h units of distance. Semivariogram is used to describe the correlation of observation sorted by location. This research discusses the theoretical Semivariogram for the Spherical, Gaussian, and Exponential Semivariogram models through the Linear Programming approach. Next, the Semivariogram parameter estimation is studied with the assumption that there are data uncertainties, called the Uncertain Semivariogram. The method used to overcome the uncertainty data is Robust Optimization. The Uncertain Semivariogram using Robust Optimization are solved using the box and ellipsoidal uncertainty set approach. The calculation of the application of the model was carried out using the R software. For the case study, the application of the model used secondary data of Lead pollutant data in the Meuse River floodplains on the borders of France and the Netherlands at 164 locations. Based on the calculation results, the Exponential theoretical Semivariogram model is obtained as the best Semivariogram model, because it has a minimum SSE. Furthermore, the application of the Uncertain Semivariogram model using Robust Optimization on the Semivariogram Exponential model of Lead pollutant data is carried out using the box and ellipsoidal uncertainty set approach which is to obtain computationally tractable results.
    Źródło:
    World Scientific News; 2020, 143; 155-169
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust Optimization Model for Truss Topology Design Problem Using Convex Programming CVX
    Autorzy:
    Shafira, Tri
    Chaerani, Diah
    Lesmana, Eman
    Powiązania:
    https://bibliotekanauki.pl/articles/1031207.pdf
    Data publikacji:
    2020
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    CVX
    Robust optimization
    Truss Topology Design
    load
    semidefinite programming
    uncertainty
    Opis:
    Topology optimization is one of the optimization applications in the field of infrastructure or truss structure design. Aiming to find the optimal connectivity bar by determining the best node leads to minimizing compliance. Robust optimization is used to conquer the uncertainty of external load parameters that are continuous and convex. The Robust Topology Optimization model uses semidefinite programming with an ellipsoidal uncertainty set. To solve the model, we use a modeling system called CVX, CVX uses the object-oriented features of MATLAB to turn it into an optimization modelling language: optimization variables can be declared and constraints and objectives specified using natural MATLAB syntax. The results of numerical simulations using CVX in the Robust Truss Topology Design (RTTD) model obtained an optimal robust solution, where the truss is resistant to load uncertainty for single-load or multi-load.
    Źródło:
    World Scientific News; 2020, 148; 27-45
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust Optimization Model for Location Transportation Problems with Ellipsoidal Uncertainty Set
    Autorzy:
    Pribadi, Diantiny Mariam
    Chaerani, Diah
    Dewanto, Stanley P.
    Supian, Sudradjat
    Subiyanto, Subiyanto
    Powiązania:
    https://bibliotekanauki.pl/articles/1062875.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Ellipsoidal uncertainty set
    Location transportation problem
    Mixed integer linear problem
    Robust Counterpart
    Robust Optimization
    Uncertainty demand
    Opis:
    The location transportation problem is a combination of location, routing and inventory facilities. The problem of transportation locations consists of strategic decisions and operational decisions. Strategy decisions consist of location and facility capacity to meet demand, while operational decisions consist of final production and optimal distribution. However, sometimes there is uncertainty in demand, which influences operational decisions. Robust Optimization is a method for solving problems that are affected by uncertainty in data. This study aims to apply single-stage with an ellipsoid approach to the problem of transportation locations with uncertainty in demand. Robust optimization through the ellipsoidal uncertainty set approach provides costs for strategic and operational decisions that tend to remain for each production period. As for the optimization model, the influence of uncertainty in demand can affect the uncertainty of strategic and operational costs.
    Źródło:
    World Scientific News; 2019, 127, 3; 296-310
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies