TY  - THES
AB  - Many of optimization problems can be decomposed into a number of easier subproblems of the same type. Then dynamic programming (DP) seems to be a natural way to obtain an optimal solution. A straightforward application of DP usually leads to algorithms whose running time heavily depends on the magnitude of the input data. It has been shown in the thesis that it is possible to improve the complexity status of straightforward DP algorithms for different optimization problems, arising in production planning and scheduling, by means
of a sensitivity analysis that allows to shrink the state space and to reduce thereby the amount of unnecessary computations. Using the suggested approach, we transform DP algorithms into polynomial ones and into so-called fully polynomial time approximation schemes.
AU  - Chubanov, Sergei
DA  - 2006
KW  - Losgrößenmodell
KW  - Reihenfolgeproblem
KW  - Algorithmus
LA  - eng
PY  - 2006
TI  - Sensitivity analysis and efficient algorithms for some economic lot-sizing and scheduling problems
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:467-2399
Y2  - 2024-12-27T08:16:23
ER  -