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Dwuetapowe stochastyczne zagadnienie rozdziału

100%
Anholcer M.
Studia Ekonomiczne
|
2015
|
vol. 235
7-17
PL
Zagadnienie rozdziału, zwane również uogólnionym zagadnieniem transportowym (Generalized Transportation Problem, GTP), pozwala modelować sytuację, w której ilość towaru opuszczającego dostawców nie jest równa ilości docierającej do odbiorców (z sytuacją taką mamy do czynienia np. w sytuacji transportu towarów szybko psujących się lub w przypadku występowania reklamacji w wyniku braków). W pracy przedstawiono model dwuetapowego GTP z losowym popytem o ciągłym rozkładzie. Zaprezentowany został algorytm rozwiązywania omawianego zagadnienia.
EN
The Generalized Transportation Problem (GTP) allows to model a situation, where the amounts of goods delivered to the destinations are not equal to the amounts leaving the supply points (this is the case i.e. when perishable goods are transported or some complaints occur because of products’ defects). In the article a model of two-stage stochastic GTP (2SGTP) has been presented, where the demands of customers are given as continuous random variables. An algorithm for such type of problems has been presented.
2
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Zastosowanie programowania stochastycznego w konstrukcji odpornych portfeli inwestycyjnych

75%
Orwat-Acedańska A., Acedański J.
Studia Ekonomiczne
|
2013
|
vol. 135
121-136
EN
The paper discusses application of stochastic programming approach to the portfolio selection problem involving estimation risk. It focuses on problems aiming at assuring that the portfolio risk does not exceed a given limit with high probability. For solving the problems the sample approximation approach is proposed for which the most important issues like a method used for generating subsamples, setting the correct number of subsamples and empirical confidence level parameter are discussed. As far as the first issue is concerned a bootstrap approach was superior to Monte Carlo method in a simulation study based on returns data of stocks listed on the Warsaw Stock Exchange. For the latter problems it is advised changing the empirical confidence level parameter instead of the number of subsamples to match expected confidence level of the stochastic program. It is also shown that the discussed approach is suitable for investors with high risk aversion.121-136
3
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Algorithm for Bi-Criteria Stochastic Generalized Transportation Problem

75%
Anholcer M.
Multiple Criteria Decision Making
|
2013
|
vol. 8
5-17
EN
The Generalized Transportation Problem is a variant of the classical Transpor-tation Problem, where the sum of the amounts of goods delivered to the destina-tion points is different from (usually lower than) the total amount sent from the sources. The Stochastic Generalized Transportation Problem (SGTP) is a version with random demand. We present the Bi-Criteria SGTP and propose an algorithm for determining the set of effective solutions.
4
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Robust Optimisation Metaheuristics for the Inventory-Allocation Problem

75%
Vizinger T., Žerovnik J.
Multiple Criteria Decision Making
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2019
|
vol. 14
128-143
EN
As an example of a successful application of a relatively simple metaheuristics for a stochastic version of a multiple criteria optimisation problem, the inventory-allocation problem is discussed. Stochastic programming is introduced to deal with the demand of end consumers. It has been shown before that simple metaheuristics, i.e., local search may be a very competitive choice for solving computationally hard optimisation problems. In this paper, robust optimisation approach is applied to select more promising initial solutions which results in a significant improvement of time complexity of the optimisation algorithms. Furthermore, it allows more flexibility in choosing the final solution that need not always be minimising the sum of costs.
5
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The analysis of robust portfolios risk in the stochastic programming method

63%
Orwat-Acedańska A.
Studia Ekonomiczne
|
2015
|
vol. 247
84-95
EN
The paper discusses an application of stochastic programming to the portfolio selection problem involving estimation risk. The paper focuses on problems where a portfolio risk should not exceed some prespecified level with high probability. Based on the real data on daily returns from American sector stock indices it is analyzed whether the stochastic programming methods truly guarantee to reach the goal regarding portfolios risk. The results show that the discussed methods indeed lower probability of exceeding the risk level compared to the classical approach. However in most cases the excess fractions were still higher from the level expected by an investor.
PL
W artykule rozważano zastosowanie metod programowania stochastycznego w problemach wyboru portfela uwzględniających ryzyko estymacji. Koncentrowano się na zadaniach, które miały na celu zapewnienie, że ryzyko portfela z dużym prawdopodobieństwem nie przekroczy zadanego poziomu. Bazując na rzeczywistych danych dotyczących dziennych stóp zwrotu amerykańskich indeksów sektorowych, analizowano, czy rozważane metody programowania stochastycznego pozwalają osiągnąć zakładany cel odnośnie do ryzyka portfela. Wyniki wskazują, że w porównaniu do klasycznego podejścia analizowane metody pozwalają zmniejszyć prawdopodobieństwo przekroczenia zadanego poziomu ryzyka. Niemniej jednak w większości przypadków odsetek przekroczeń w dalszym ciągu był wyższy od zakładanego.
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