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Wyświetlanie 1-15 z 21
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
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:
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:
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:
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 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:
Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment
Autorzy:
Golpîra, H.
Powiązania:
https://bibliotekanauki.pl/articles/406601.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
supply chain management
production-distribution planning
conditional value at risk
bilevel programming
robust optimization
KKT conditions
zarządzanie łańcuchem dostaw
planowanie produkcji
planowanie dystrybucji
optymalizacja
warunki KKT
Opis:
This paper introduces the problem of designing a single-product supply chain network in an agile manufacturing setting under a vendor managed inventory (VMI) strategy to seize a new market oppor-tunity. The problem addresses the level of risk aversion of the retailer when dealing with the uncertainty of market related information through a conditional value at risk (CVaR) approach. This approach leads to a bilevel programming problem. The Karush–Kuhn–Tucker (KKT) conditions are employed to trans-form the model into a single-level, mixed-integer linear programming problem by considering some relaxations. Since realizations of imprecisely known parameters are the only information available, a data-driven approach is employed as a suitable, more practical, methodology of avoiding distribu-tional assumptions. Finally, the effectiveness of the proposed model is demonstrated through a numer-ical example
Źródło:
Operations Research and Decisions; 2017, 27, 1; 21-41
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
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:
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:
Loopshaping of motor torque controller
Autorzy:
Sieklucki, G.
Powiązania:
https://bibliotekanauki.pl/articles/229950.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
electric drive
II2 controller
robust control
stability region
parametric optimization
nonlinear programming
waterbed effect
weighted sensitivity
modulus criterion
Opis:
The controller synthesis problem of the motor torque is presented. The tuning of the II2 controller parameters of the electromagnetic motor torque is introduced. The results are obtained by applying the weighted sensitivity method (nominal performance) which is the optimization in H∞ space. The waterbed effect for some weighting functions is presented. The results, which are obtained by a parametric optimization (nonlinear programming), are analysed by the calculations of the stability margins.
Źródło:
Archives of Control Sciences; 2013, 23, 2; 213-228
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance of robust portfolio optimization in crisis periods
Autorzy:
Balcilar, M.
Ozun, A.
Powiązania:
https://bibliotekanauki.pl/articles/205665.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
robust control procedures
RobustRisk
portfolio optimization
Monte Carlo simulation
global crisis
Opis:
We examin empirical performances of two alterna- tive robust optimization models, namely the worst-case conditional value-at-risk (worst-case CVaR) model and the nominal conditional value-at-risk (CVaR) model in crisis periods. Both models are based on historical value-at-risk methodology. These performances are compared by using a portfolio constructed on the basis of daily clos- ing values of different stock indices in developed markets using data from 1990 to 2013. An empirical evidence is produced with Ro- bustRisk software application. Both a Monte-Carlo simulation and an out-of-sample test show that robust optimization with worst-case CVaR model outperforms the nominal CVaR model in the crisis peri- ods. However, the trade-off between model misspecification risk and return maximization depending on the market movements should be optimized in a robust model selection.
Źródło:
Control and Cybernetics; 2013, 42, 4; 855-871
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ply thickness tolerances in stacking sequence optimization of multilayered laminate plates
Autorzy:
Latalski, J.
Powiązania:
https://bibliotekanauki.pl/articles/279654.pdf
Data publikacji:
2013
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
laminate composite structures
optimization
manufacturing tolerances
robust design
structural stability
Opis:
The paper deals with the impact of manufacturing tolerances of plies thicknesses on optimal design of multi-layered laminated plates in compression. It is assumed that the considered tolerances are represented by the maximum acceptable deviation of every individual ply thickness from its nominal design value. The robustness of the optimum is achieved diminishing the buckling load amplitude factor by the product of arbitrary assumed tolerances and appropriate sensitivities. The discussed optimization problem is solved numerically by the direct enumeration method. The proposed approach is illustrated with examples of the rectangular multi-layered laminated plate design under uni- and biaxial compression. The achieved results emphasise the robustness of the proposed method compared to the approaches with ignored tolerances.
Źródło:
Journal of Theoretical and Applied Mechanics; 2013, 51, 4; 1039-1052
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Preference-Driven Multiobjective Optimization Using Robust Ordinal Regression for Cone Contraction
Autorzy:
Kadziński, Miłosz
Słowiński, Roman
Powiązania:
https://bibliotekanauki.pl/articles/578592.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Odporne metody statystyczne
Optymalizacja wielokryterialna
Podejmowanie decyzji
Decision making
Multiple criteria optimization
Robust statistical methods
Opis:
We present a new interactive procedure for multiobjective optimization problems (MOO), which involves robust ordinal regression in contraction of the preference cone in the objective space. The most preferred solution is achieved by means of a systematic dialogue with the decision maker (DM) during which (s)he species pairwise comparisons of some non-dominated solutions from a current sample. The origin of the cone is located at a reference point chosen by the DM. It is formed by all directions of isoquants of the achievement scalarizing functions compatible with the pairwise comparisons of non-dominated solutions provided by the DM. The compatibility is assured by robust ordinal regression, i.e. the DM's statements concerning strict or weak preference relations for pairs of compared solutions are represented by all compatible sets of weights of the achievement scalarizing function. In successive iterations, when new pairwise comparisons of solutions are provided, the cone is contracted and gradually focused on a subregion of the Pareto optimal set of greatest interest. The DM is allowed to change the reference point and the set of pairwise comparisons at any stage of the method. Such preference information does not need much cognitive e ort on the part of the DM. The phases of preference elicitation and cone contraction alternate until the DM nds at least one satisfactory solution, or there is no such solution for the current problem setting.
Źródło:
Multiple Criteria Decision Making; 2013, 8; 67-83
2084-1531
Pojawia się w:
Multiple Criteria Decision Making
Dostawca treści:
Biblioteka Nauki
Artykuł
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:
Generalized ordered linear regression with regularization
Autorzy:
Łęski, J.
Henzel, N.
Powiązania:
https://bibliotekanauki.pl/articles/201591.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
linear regression
IRLS
OWA
conjugate gradient optimization
robust methods
Opis:
Linear regression analysis has become a fundamental tool in experimental sciences. We propose a new method for parameter estimation in linear models. The 'Generalized Ordered Linear Regression with Regularization' (GOLRR) uses various loss functions (including the o-insensitive ones), ordered weighted averaging of the residuals, and regularization. The algorithm consists in solving a sequence of weighted quadratic minimization problems where the weights used for the next iteration depend not only on the values but also on the order of the model residuals obtained for the current iteration. Such regression problem may be transformed into the iterative reweighted least squares scenario. The conjugate gradient algorithm is used to minimize the proposed criterion function. Finally, numerical examples are given to demonstrate the validity of the method proposed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 481-489
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
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