## An improved algorithm for dynamic lot sizing problem with learning effect in setups |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Common terms and phrases

adjacent Aggarwal and Park Algorithm DLSPL algorithm for DLSPL approach Chand characterization Cl This lemma complexity Computational conclusions consider constant setup cost contradiction cost h cumulative number decreasing deﬁne deﬁnition demand denote the total dominated dynamic lot sizing Dynamic Programming Federgruen and Tzur ﬁred ﬁxed point following lemma formulation H K,_ Hoesel and Kolen Ifi 3 m(i implies improvement increasing function inequality interval inventory holding cost LB,_(lc leads learning effect lemma says length of horizon linear lot sizing problem lower bound minima minimum modiﬁed algorithm number of setups objective value obtain optimal production optimal solution output paper period of setup present problem P(K,_ production plan Proof reduction repeat Solve P(K,_ signiﬁcant similar sizing problem Solution Algorithm solved in O(T speciﬁed stage Suppose timal total number Wagelmans Wagner and Whitin Wagner-Whitin lotsizing problem Whitin lotsizing problems worst