Scope for industrial applications of production scheduling models and solution methods

By Iiro Harjunkoski, Christos T. Maravelias, P. Bongers, P. Castro, S. Engell, Ignacio E. Grossmann, John N. Hooker, Carlos A. Méndez, G. Sand, J. Wassick. Computers and Chemical Engineering, 2014

499 citations recorded by the source corpus.

Abstract This paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.

Subfields: Control and Systems Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/684ccdcbba32b792bceb8ab13f69abca6f48cefc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Marina Ivanova
2. Dmitry A. Ivanov
3. Boris V. Sokolov
4. Alexandre Dolgui

In Industrial and Manufacturing Engineering

1. Dmitry A. Ivanov
2. Boris V. Sokolov
3. Alexandre Dolgui
4. Hendrik Birkel
5. Alexander Spieske

Citations in the corpus

• Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives (2016, unknown): “For recent reviews of works on production scheduling in PSE, we refer to Méndez et al. (2006), Maravelias (2012), and Harjunkoski et al. (2014).”
• A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0 (2016, background): “The studies by Sarimveis et al. (2008) and Harjunkoski et al. (2014) showed a wide range of advantages regarding the application of control-theoretic models in combination with other techniques to production and logistics.”