Please use this identifier to cite or link to this item: https://doi.org/10.48548/pubdata-1171
Resource typeWorking Paper
Title(s)Production Planning with Simulated Annealing
DOI10.48548/pubdata-1171
Handle20.500.14123/1234
CreatorUrban, Karsten-Patrick
AbstractCombinatorial 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.
LanguageEnglish
KeywordsSimulated Annealing; Flow-Shop-Scheduling; Lokales Suchverfahren; Produktionsplanung; Reihenfolgeplanung; Flow-Shop-Problem; Maschinenbelegungsplanung
Year of publication in PubData2003
Publishing typeFirst publication
Publication versionDraft
Date issued2003-12-22
Creation contextResearch
Published byMedien- und Informationszentrum, Leuphana Universität Lüneburg
Files in This Item:
File SizeFormat 

simuan.pdf
MD5: f872c1b0c466785e97bca376bc711452
License:  Nutzung nach Urheberrecht
open-access

101.51 kB

Adobe PDF
View/Open

Items in PubData are protected by copyright, with all rights reserved, unless otherwise indicated.

Citation formats
Access statistics

Page view(s): 36

Download(s): 3