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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-article-BAT5-0013-0002

Czasopismo

Control and Cybernetics

Tytuł artykułu

Approximating the solution of a dynamic, stochastic multiple knapsack problem

Autorzy Hartman, J. C.  Perry, T. C. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN We model an environment where orders arrive probabilistically over time, with their revenues and capacity requirements becoming known upon arrival. The decision is whether to accept an order, receiving a reward and reserving capacity, or reject an order, freeing capacity for possible future arrivals. We model the dynamic, stochastic multiple knapsack problem (DSMKP) with stochastic dynamic programming (SDP). Multiple knapsacks are used as orders may stay in the system for multiple periods. As the state space grows exponentially in the number of knapsacks and the number of possible orders per period, we utilize linear programming and duality to quickly approximate the end-of-horizon values for the SDP. This helps mitigate end-of-study effects when solving the SDP directly, allowing for the solution of larger problems and leading to increased quality in solutions.
Słowa kluczowe
PL programowanie liniowe   dualność  
EN stochastic dynamic programming   approximate dynamic programming   linear programming   duality  
Wydawca Systems Research Institute, Polish Academy of Sciences
Czasopismo Control and Cybernetics
Rocznik 2006
Tom Vol. 35, no 3
Strony 535--550
Opis fizyczny Bibliogr. 11 poz., rys., wykr.
Twórcy
autor Hartman, J. C.
autor Perry, T. C.
  • Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania, USA
Bibliografia
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PERRY, T.C. and HARTMAN, J.C. (2004) Allocating manufacturing capacity by solving a dynamic, stochastic, multiple knapsack problem. Technical Report T004-009, Industrial and Systems Engineering, Lehigh University, Bethlehem, PA.
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Kolekcja BazTech
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