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Wyświetlanie 1-10 z 21
Tytuł:
A computational study of approximation algorithms for a minmax resource allocation problem
Autorzy:
Przybysławski, B.
Kasperski, A.
Powiązania:
https://bibliotekanauki.pl/articles/406619.pdf
Data publikacji:
2012
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
discrete optimization
robust optimization
resource allocation
approximation algorithms
Opis:
A basic resource allocation problem with uncertain costs has been discussed. The problem is to minimize the total cost of choosing exactly p items out of n available. The uncertain item costs are specified as a discrete scenario set and the minmax criterion is used to choose a solution. This problem is known to be NP-hard, but several approximation algorithms exist. The aim of this paper is to investigate the quality of the solutions returned by these approximation algorithms. According to the results obtained, the randomized algorithms described are fast and output solutions of good quality, even if the problem size is large.
Źródło:
Operations Research and Decisions; 2012, 22, 2; 35-43
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Perturbation algorithm for a minimax regret minimum spanning tree problem
Autorzy:
Makuchowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/406452.pdf
Data publikacji:
2014
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
discrete optimization
robust optimization
perturbation algorithms
minimax regret
Opis:
The problem of finding a robust spanning tree has been analysed. The problem consists of determining a minimum spanning tree of a graph with uncertain edge costs. We should determine a spanning tree that minimizes the difference in costs between the tree selected and the optimal tree. While doing this, all possible realizations of the edge costs should be taken into account. This issue belongs to the class of NP-hard problems. In this paper, an algorithm based on the cost perturbation method and adapted to the analysed problem has been proposed. The paper also contains the results of numerical experiments testing the effectiveness of the proposed algorithm and compares it with algorithms known in the literature. The research is based on a large number of various test examples taken from the literature.
Źródło:
Operations Research and Decisions; 2014, 24, 1; 37-49
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
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
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:
The art and science of modeling decision-making under severe uncertainty
Autorzy:
Sniedovich, M.
Powiązania:
https://bibliotekanauki.pl/articles/375963.pdf
Data publikacji:
2007
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
mathematical modeling
severe uncertainty
maximin
worst-case analysis
robust optimization
info-gap
Opis:
For obvious reasons, models for decision-making under severe uncertainty are austere. Simply put, there is precious little to work with under these conditions. This fact highlights the great importance of utilizing in such cases the ingredients of the mathematical model to the fullest extent, which in turn brings under the spotlight the art of mathematical modeling. In this discussion we examine some of the subtle considerations that are called for in the mathematical modeling of decision-making under severe uncertainty in general, and worst-case analysis in particular. As a case study we discuss the lessons learnt on this front from the Info-Gap experience.
Źródło:
Decision Making in Manufacturing and Services; 2007, 1, 1-2; 111-136
1896-8325
2300-7087
Pojawia się w:
Decision Making in Manufacturing and Services
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
Tytuł:
Charakterystyka optymalizacji odpornej problemu najkrótszej ścieżki w obszarach zurbanizowanych
Analysis of robust optimization for shortest path problem in urban areas
Autorzy:
Kubek, Daniel
Powiązania:
https://bibliotekanauki.pl/articles/587302.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Elastyczne okna czasowe
Optymalizacja odporna
Problem najkrótszej ścieżki
Robust optimization
Shortest path problem
Soft time windows
Opis:
Niniejszy artykuł przedstawia problematykę wyznaczania ścieżek dla pojazdów poruszających się w sieci drogowej miasta. Ścieżki te zostały wyznaczone w oparciu o optymalizację odporną, która uwzględnia możliwość wystąpienia wahań od wartości oczekiwanej czasów przejazdu na odcinkach sieci drogowej. Poruszone zagadnienie popularnie znane jest jako problem najkrótszej ścieżki z niepewnymi czasami przejazdów (robust shortest path problem). Odporny model matematyczny problemu najkrótszej ścieżki został rozwiązany za pomocą metody, która zamienia oryginalny problem na deterministyczny odpowiednik programowania liniowego. Odpowiednik ten jest uzyskiwany przez przyjęcie założenia, że zmienna decyzyjna jest funkcją afiniczną, która zależy od realizacji niepewności danych. Niepewność jest zdefiniowana na podstawie odchylenia standardowego czasu przejazdu na poszczególnym odcinku. Parametry te są wykorzystane do opisu rodziny rozkładów prawdopodobieństwa, zgodnie z którymi wartość niepewności danych będzie realizowana. Zalety stosowania optymalizacji odpornej oraz charakterystyka problemu zostały zaprezentowane na rzeczywistej sieci drogowej miasta Krakowa.
The paper addresses the shortest path problem for vehicles traversing the road network of the city. The paths have been determinate based on the robust optimization theory, which take into account the data uncertainty. The problem is known as robust shortest path problem. Formulation of robust mathematical model is solved by transforming the robust model into a deterministic counterpart. Deterministic counterpart is obtained by assumption that variables are affinely dependent on primitives uncertainty. Uncertainty set is defined as affine function of standard deviation of sections travel time. These parameters are used to describe a family of probability distributions under which the value of the uncertainty of the data will be implemented. The advantages, analysis and the characteristics of robust approach are presented on a real example – the road network of Cracow.
Źródło:
Studia Ekonomiczne; 2015, 235; 132-143
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Necessary optimality conditions for robust nonsmooth multiobjective optimization problems
Autorzy:
Gadhi, Nazih Abderrazzak
Ohda, Mohamed
Powiązania:
https://bibliotekanauki.pl/articles/2183482.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
convexificator
directional constraint qualification
efficient solution
optimality conditions
robust multiobjective optimization
Opis:
This paper deals with a robust multiobjective optimization problem involving nonsmooth/nonconvex real-valued functions. Under an appropriate constraint qualification, we establish necessary optimality conditions for weakly robust efficient solutions of the considered problem. These optimality conditions are presented in terms of Karush-Kuhn-Tucker multipliers and convexificators of the related functions. Examples illustrating our findings are also given.
Źródło:
Control and Cybernetics; 2022, 51, 3; 289--302
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-10 z 21

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