Multi-Level Lot Sizing and Scheduling: Methods for by Alf Kimms

By Alf Kimms

This booklet is the result of my examine within the box of multi­ levellot sizing and scheduling which began in may well 1993 on the Christian-Albrechts-University of Kiel (Germany). in this time i found a growing number of attention-grabbing features ab out this topic and that i needed to research that no longer each promising proposal will be completely evaluated through one individual on my own. however, i'm now within the place to offer a few effects that are speculated to be valuable for destiny endeavors. considering that April 1995 the paintings was once performed with partial help from the study undertaking no. Dr 170/4-1 from the "Deutsche For­ schungsgemeinschaft" (D FG). the rest area during this preface shaH be devoted to those that gave me precious help: First, permit me exhibit my deep gratitude in the direction of my thesis advert­ visor Prof. Dr. Andreas Drexl. He definitely is a truly striking consultant. with out his regular feedback, this paintings do not have come that a ways. regardless of his scarce time capacities, he by no means rejected proof-reading draft models of operating papers, and he used to be regularly keen to debate new principles - the great as weH because the undesirable ones. He and Prof. Dr. Gerd Hansen refereed this thesis. i'm in­ debted to either for his or her review. i'm additionally owing whatever to Dr. Knut Haase. when you consider that we al­ so much by no means had an identical opinion while discussing definite lot sizing features, his reviews and feedback gave stimulating input.

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Extra resources for Multi-Level Lot Sizing and Scheduling: Methods for Capacitated, Dynamic, and Deterministic Models

Example text

Vickery and Markland [ViMa86] report about experiences in using MIP-model formulations being solved with standard solvers in a real-world situation. Their field of application is a pharmaceutical company. Zäpfel and Attmann [ZäAt80] present some kind of a tutorial for multi-level lot sizing. They assurne several serial gozintostructures being processed in parallel. A MIP-model is given on the basis of which a fixed charge problem reformulation and examples are discussed. Ramsey and Rardin [RaRa83] consider serial structures and propose several heuristics.

Positive and integral lead time of item j. Unique initial setup state. 2: Parameters for the PLSP-MM Yjt E {O,l} j = 1, ... ,J t = 1, ... 8) = 1, ... ,J = 1, ... 1) is to minimize the sum of setup and holding costs. 2) are the inventory balances. At the end of aperiod t we have in inventory what was in there at the end of period t - 1 plus what is produced minus external and internal demand. To fulfill internal demand we must respect positive lead 34 CHAPTER 3. PROBLEM SPECIFICATIONS times. 3) guarantee so.

And, the optimum objective function value of the preprocessed instance equals the optimum objective function value of the original instance. In the multi-level case there are some strings attached which do not keep things that easy. A small example certainly brings this out best. Suppose J = 2 items are manufactured on a single machine. 2. Let the planning horizon be T = 4. 4. Points worth to be highlighted are that the machine is initially set up for item 1 (Yno = 1) and that there is a positive initial inventory for item 2 (120 = 10).

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