3 citations · 8 across the 12 of their papers we have counts for
30 papers
A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem
Matthew Bold, Marc Goerigk
This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider…
Benchmarking Problems for Robust Discrete Optimization
Marc Goerigk, Mohammad Khosravi
Robust discrete optimization is a highly active field of research where a plenitude of combinations between decision criteria, uncertainty sets and underlying nominal problems are…
Data-Driven Robust Optimization using Unsupervised Deep Learning
Marc Goerigk, Jannis Kurtz
Robust optimization has been established as a leading methodology to approach decision problems under uncertainty. To derive a robust optimization model, a central ingredient is to…
Robust Optimization Approaches for Routing and Scheduling of Multi-Skilled Teams under Uncertain Job Skill Requirements
Yulia Anoshkina, Marc Goerigk, Frank Meisel
We consider a combined problem of teaming and scheduling of multi-skilled employees that have to perform jobs with uncertain qualification requirements. We propose two modeling app…
Multistage Robust Discrete Optimization via Quantified Integer Programming
Marc Goerigk, Michael Hartisch
Decision making needs to take an uncertain environment into account. Over the last decades, robust optimization has emerged as a preeminent method to produce solutions that are imm…
Robust Combinatorial Optimization with Locally Budgeted Uncertainty
Marc Goerigk, Stefan Lendl
Budgeted uncertainty sets have been established as a major influence on uncertainty modeling for robust optimization problems. A drawback of such sets is that the budget constraint…