Meta Heuristics for Dynamic Machine Scheduling: A Review of Research Efforts and Industrial Requirements

Simon Anderer, Thanh-Ha Vu, Bernd Scheuermann, Sanaz Mostaghim

2018

Abstract

This paper presents a survey on the state-of-the-art of dynamic machine scheduling problems. For this purpose, 82 papers have been examined according to the underlying scheduling models and assumptions, the source and implementation of uncertainty and dynamics as well as the applied solution methods and optimization criteria. Furthermore, the integration of machine scheduling into the functional levels of a company is outlined and the essential requirements for dynamic machine scheduling in modern industrial environments are identified. On this basis, the most prevalent gaps, the main challenges, and conclusions for future research are pointed out.

Paper Citation

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI
TI - Meta Heuristics for Dynamic Machine Scheduling: A Review of Research Efforts and Industrial Requirements
SN - 978-989-758-327-8
AU - Anderer S.
AU - Vu T.
AU - Scheuermann B.
AU - Mostaghim S.
PY - 2018
SP - 192
EP - 203
DO - 10.5220/0006930701920203
PB - SciTePress

in Harvard Style

Anderer S., Vu T., Scheuermann B. and Mostaghim S. (2018). Meta Heuristics for Dynamic Machine Scheduling: A Review of Research Efforts and Industrial Requirements. In Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI; ISBN 978-989-758-327-8, SciTePress, pages 192-203. DOI: 10.5220/0006930701920203

in Bibtex Style

@conference{ijcci18,
author={Simon Anderer and Thanh-Ha Vu and Bernd Scheuermann and Sanaz Mostaghim},
title={Meta Heuristics for Dynamic Machine Scheduling: A Review of Research Efforts and Industrial Requirements},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI},
year={2018},
pages={192-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006930701920203},
isbn={978-989-758-327-8},
}