A rolling-horizon approach for multi-period optimization

Glomb L, Liers F, Rösel F (2021)

Publication Language: English

Publication Status: Accepted

Publication Type: Journal article

Future Publication Type: Journal article

Publication year: 2021


Publisher: Elsevier

Edited Volumes: European Journal of Operational Research

Series: unbekannt

City/Town: Amsterdam, Niederlande

Book Volume: unbekannt

Edition: unbekannt

Journal Issue: unbekannt

URI: https://www.sciencedirect.com/science/article/abs/pii/S0377221721006536

DOI: 10.1016/j.ejor.2021.07.043


Mathematical optimization problems including a time dimension abound. For example, logistics,

process optimization and production planning tasks must often be optimized for a range of time

periods. Usually, these problems incorporating time structure are very large and cannot be solved to global

optimality by modern solvers within a reasonable period of time. Therefore, the so-called rolling-horizon

approach is often adopted. This approach aims to solve the problem periodically, including additional

information from proximately following periods. In this paper, we first investigate several drawbacks of

this approach and develop an algorithm that compensates for these drawbacks both theoretically and

practically. As a result, the rolling horizon decomposition methodology is adjusted to enable large scale

optimization problems to be solved efficiently. In addition, we introduce conditions that guarantee the

quality of the solutions. We further demonstrate the applicability of the method to a variety of challenging

optimization problems. We substantiate the findings with computational studies on the lot-sizing problem

in production planning, as well as for large-scale real-world instances of the tail-assignment problem in

aircraft management. It proves possible to solve large-scale realistic tail-assignment instances efficiently,

leading to solutions that are at most a few percent away from a globally optimum solution.

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How to cite


Glomb, L., Liers, F., & Rösel, F. (2021). A rolling-horizon approach for multi-period optimization. European Journal of Operational Research, unbekannt(unbekannt). https://doi.org/10.1016/j.ejor.2021.07.043


Glomb, Lukas, Frauke Liers, and Florian Rösel. "A rolling-horizon approach for multi-period optimization." European Journal of Operational Research unbekannt.unbekannt (2021).

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