Please use this identifier to cite or link to this item:
https://doi.org/10.48548/pubdata-1171
| Resource type | Working Paper |
| Title(s) | Production Planning with Simulated Annealing |
| DOI | 10.48548/pubdata-1171 |
| Handle | 20.500.14123/1234 |
| Creator | Urban, Karsten-Patrick |
| Abstract | Combinatorial optimization is still one of the biggest mathematical challenges if you plan and organize the run-ning of a business. Especially if you organize potential factors or plan the scheduling and sequencing of opera-tions you will often be confronted with large-scaled combinatorial optimization problems. Furthermore it is very difficult to find global optima within legitimate time limits, because the computational effort of such problems rises exponentially with the problem size. Nowadays several approximation algorithms exist that are able to solve this kind of problems satisfactory. These algorithms belong to a special group of solution methods which are called local search algorithms. This article will introduce the topic of simulated annealing, one of the most efficient local search strategies. This article summarizes main aspects of the guest lecture Combinatorial Optimi-zation with Local Search Strategies, which was held at the University of Ioannina in Greece in June 1999. |
| Language | English |
| Keywords | Simulated Annealing; Flow-Shop-Scheduling; Lokales Suchverfahren; Produktionsplanung; Reihenfolgeplanung; Flow-Shop-Problem; Maschinenbelegungsplanung |
| Year of publication in PubData | 2003 |
| Publishing type | First publication |
| Publication version | Draft |
| Date issued | 2003-12-22 |
| Creation context | Research |
| Published by | Medien- und Informationszentrum, Leuphana Universität Lüneburg |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
simuan.pdf License: Nutzung nach Urheberrecht open-access | 101.51 kB | Adobe PDF | View/Open |
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