Abstract
In this chapter we study a robust resource allocation problem that minimizes the worst-case makespan. As in the previous chapters, we assume that the resource allocation is a here-and-now decision, whereas the task start times are modeled as a wait-and-see decision that may depend on random parameters affecting the task durations. In the terminology of Sect. 2.2.2, we therefore study a two-stage robust optimization problem. In contrast to its stochastic counterpart, the complexity of the robust resource allocation problem has been unknown for a long time [Hag88]. The majority of the solution approaches presented in the literature determine suboptimal solutions without bounding the incurred optimality gap.
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Notes
- 1.
As we will see in Sect. 6.2.3, evaluating the worst-case makespan of the optimal second-stage policy in \(\mathcal{R}\mathcal{T}\mathcal{N}\) constitutes a difficult problem even for fixed x ∈ X.
- 2.
ISCAS 85 benchmark circuits: http://www.cbl.ncsu.edu/benchmarks.
- 3.
CONOPT homepage: http://www.conopt.com.
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© 2012 Springer-Verlag Berlin Heidelberg
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Wiesemann, W. (2012). Minimization of the Worst-Case Makespan. In: Optimization of Temporal Networks under Uncertainty. Advances in Computational Management Science, vol 11. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23427-9_6
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DOI: https://doi.org/10.1007/978-3-642-23427-9_6
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