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Integrating Sequencing and Scheduling: A Generic Approach with Two Exemplary Industrial Applications

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9220))

Abstract

A huge number of problems in production planning ask for a somewhat good processing sequence. While all those problems share the common sequencing aspect, the underlying side constraints, and hence, the related scheduling decisions, are highly problem-specific. We propose a generic algorithmic framework which aims at separating the side constraints from the general sequencing decisions. This allows us to only focus on the optimization problem that remains when the processing sequence is already decided—in many cases yet another NP-hard problem. Compared to the overall problem, this subproblem is far more manageable. In cooperation with industry, our approach has been applied to problems of planning (sheet metal) coil coating lines and dairy filling lines, respectively. For the subproblem of the coil coating problem, we could observe a close relation to the maximum weight independent set problem on a special class of multiple-interval graphs. Thorough insights into this problem were finally the basis for achieving a makespan reduction of over \(13\%\) on average for the coil coating line of our industrial partner. For the less complex dairy problem, our solutions were on par with the manual production plans in use at the production site of our project partner. We could show that this solution is almost optimal, i.e., within a factor of 1.02 times a lower bound.

Supported by the German Research Foundation (DFG) as part of the Priority Program “Algorithm Engineering.”.

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Notes

  1. 1.

    http://challenge.roadef.org/2005/en/.

  2. 2.

    This success has made this contribution a finalist of the 2009 EURO Excellence in Practice Award.

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Correspondence to Rolf H. Möhring .

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Höhn, W., Möhring, R.H. (2016). Integrating Sequencing and Scheduling: A Generic Approach with Two Exemplary Industrial Applications. In: Kliemann, L., Sanders, P. (eds) Algorithm Engineering. Lecture Notes in Computer Science(), vol 9220. Springer, Cham. https://doi.org/10.1007/978-3-319-49487-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-49487-6_10

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