Optimization Networks for Real-World Production and Logistics Problems

Viktoria Hauder; Andreas Beham; Stefan Wagner; Michael Affenzeller

Optimization Networks for Real-World Production and Logistics Problems

Viktoria Hauder, Andreas Beham, Stefan Wagner, Michael Affenzeller

Institute of Formal Models and Verification

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

With the continuous advancement of industry 4.0, also in the area of production and logistics optimization, a more holistic consideration of problems is required. Therefore, in contrary to the traditional sequential optimization approach in the area of operations research, in this paper, an integrated solution approach called optimization networks (ON) is presented. In an ON, multiple problem models get connected and optimized by an evolutionary solution algorithm. By having several optimization runs, in which the results of the preceding optimizations are considered, opportunity costs which could arise out of a traditional sequential optimization approach, are avoided.

Original language	English
Title of host publication	GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Berlin, Germany, Deutschland, 2017
Number of pages	4
Publication status	Published - 2017

Fields of science

102 Computer Sciences
102001 Artificial intelligence
102011 Formal languages
102022 Software development
102031 Theoretical computer science
603109 Logic
202006 Computer hardware

JKU Focus areas

Computation in Informatics and Mathematics

Cite this

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title = "Optimization Networks for Real-World Production and Logistics Problems",

abstract = "With the continuous advancement of industry 4.0, also in the area of production and logistics optimization, a more holistic consideration of problems is required. Therefore, in contrary to the traditional sequential optimization approach in the area of operations research, in this paper, an integrated solution approach called optimization networks (ON) is presented. In an ON, multiple problem models get connected and optimized by an evolutionary solution algorithm. By having several optimization runs, in which the results of the preceding optimizations are considered, opportunity costs which could arise out of a traditional sequential optimization approach, are avoided.",

author = "Viktoria Hauder and Andreas Beham and Stefan Wagner and Michael Affenzeller",

year = "2017",

language = "English",

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T1 - Optimization Networks for Real-World Production and Logistics Problems

AU - Hauder, Viktoria

AU - Beham, Andreas

AU - Wagner, Stefan

AU - Affenzeller, Michael

PY - 2017

Y1 - 2017

N2 - With the continuous advancement of industry 4.0, also in the area of production and logistics optimization, a more holistic consideration of problems is required. Therefore, in contrary to the traditional sequential optimization approach in the area of operations research, in this paper, an integrated solution approach called optimization networks (ON) is presented. In an ON, multiple problem models get connected and optimized by an evolutionary solution algorithm. By having several optimization runs, in which the results of the preceding optimizations are considered, opportunity costs which could arise out of a traditional sequential optimization approach, are avoided.

AB - With the continuous advancement of industry 4.0, also in the area of production and logistics optimization, a more holistic consideration of problems is required. Therefore, in contrary to the traditional sequential optimization approach in the area of operations research, in this paper, an integrated solution approach called optimization networks (ON) is presented. In an ON, multiple problem models get connected and optimized by an evolutionary solution algorithm. By having several optimization runs, in which the results of the preceding optimizations are considered, opportunity costs which could arise out of a traditional sequential optimization approach, are avoided.

M3 - Conference proceedings

BT - GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Berlin, Germany, Deutschland, 2017

ER -