Production planning with simulated annealing

Publikation: Bücher und AnthologienMonografienForschung

Standard

Production planning with simulated annealing. / Urban, Karsten-Patrick.
Lüneburg: Universität Lüneburg, 2003.

Publikation: Bücher und AnthologienMonografienForschung

Harvard

Urban, K-P 2003, Production planning with simulated annealing. Universität Lüneburg, Lüneburg.

APA

Urban, K.-P. (2003). Production planning with simulated annealing. Universität Lüneburg.

Vancouver

Urban KP. Production planning with simulated annealing. Lüneburg: Universität Lüneburg, 2003.

Bibtex

@book{2e865879e88e4a49afc0ad0ab1a4aab1,
title = "Production planning with simulated annealing",
abstract = "Lokales Suchverfahren, Produktionsplanung, Reihenfolgeplanung, Flow-Shop-Problem, Maschinenbelegungsplanung, Simulated Annealing, Flow-Shop-Scheduling. 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",
keywords = "Management studies",
author = "Karsten-Patrick Urban",
note = "[Electronic ed.]",
year = "2003",
language = "English",
publisher = "Universit{\"a}t L{\"u}neburg",

}

RIS

TY - BOOK

T1 - Production planning with simulated annealing

AU - Urban, Karsten-Patrick

N1 - [Electronic ed.]

PY - 2003

Y1 - 2003

N2 - Lokales Suchverfahren, Produktionsplanung, Reihenfolgeplanung, Flow-Shop-Problem, Maschinenbelegungsplanung, Simulated Annealing, Flow-Shop-Scheduling. 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

AB - Lokales Suchverfahren, Produktionsplanung, Reihenfolgeplanung, Flow-Shop-Problem, Maschinenbelegungsplanung, Simulated Annealing, Flow-Shop-Scheduling. 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

KW - Management studies

UR - http://www.gbv.de/dms/lueneburg/LG/OPUS/2003/217/pdf/simuan.pdf

M3 - Monographs

BT - Production planning with simulated annealing

PB - Universität Lüneburg

CY - Lüneburg

ER -

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