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Wyświetlanie 1-2 z 2
Tytuł:
Selection of lease contracts in an asset-backed securitization : a real case analysis
Autorzy:
Mansini, R.
Speranza, M.
Powiązania:
https://bibliotekanauki.pl/articles/206882.pdf
Data publikacji:
1999
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
programowanie liniowe
investment
lease contracts
multidimensional knapsack problem
securities trading
securitization
Opis:
Asset-backed securities represent one of the most attractive financial novelties for institutional investors. More precisely, asset-backed securities are the output of a complex financial operation, so-called securitization, in which bonds are issued to finance a collection of assets in such a way that the bonds issue design is integrated with the funded assets. We consider a real case of securitization, in which the assets are lease contracts. Through the market issuance of tranches of notes a bank (seller) receives funds from a factor (purchaser) and pay them back in terms of pools of credits associated with lease contracts. In this paper we analyze the problem of selecting the most convenient collection of lease contracts (assets) for the seller to hand over to the purchaser. A 0-1 linear programming model is presented which is shown to be equivalent to a 0-1 Multidimensional Knapsack Problem. Heuristic solution procedures are proposed and computational results based on data from the discussed real case are presented.
Źródło:
Control and Cybernetics; 1999, 28, 4; 739-754
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Tabu search: global intensification using dynamic programming
Autorzy:
Wilbaut, C.
Hanafi, S.
Fréville, A.
Balev, S.
Powiązania:
https://bibliotekanauki.pl/articles/970871.pdf
Data publikacji:
2006
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
programowanie dynamiczne
tabu search
dynamic programming
global intensification
multidimensional 0-1 knapsack problem
Opis:
Tabu search has proven highly successful in solving hard combinatorial optimization problems. In this paper, we propose a hybrid method that combines adaptive memory, sparse dynamic programming, and reduction techniques to reduce and explore the search space. Our approach starts with a bi-partition of the variables, involving a small core problem, which never exceeds 15 variables, solved using the "forward" phase of the dynamic programming procedure. Then, the remaining subspace is explored using tabu search, and each partial solution is completed with the information stored during the forward phase of dynamic programming. Our approach can be seen as a global intensification mechanism, since at each iteration, the move evaluations involve solving a reduced problem implicitly. The proposed specialized tabu search approach was tested in the context of the multidimensional 0-1 knapsack problem. Our approach was compared to ILOG's commercial product CPLEX and to the corresponding "pure" tabu search (i.e., without a core problem) for various sets of test problems available in OR-libraries. The results are encouraging. In particular, this enhances the robustness of the approach, given that it performs better than the corresponding pure tabu search most of the time. Moreover, our approach compares well with CPLEX when the number of variables is large; it is able to provide elite feasible solutions in a very reasonable amount of computational time.
Źródło:
Control and Cybernetics; 2006, 35, 3; 579-598
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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