Min-Conflicts Heuristic for Multi-Mode Resource-Constrained Projects Scheduling

We investigate solving of Multi-Mode Resource-Constrained Multiple Projects Scheduling Problem by heuristic techniques. A new method based on Min-Conflicts heuristic is proposed and evaluated. The main idea is to efficiently explore the neighborhood of current solution based on conflicts of activities that share the same resources. This technique is further used within the Iterated Local Search framework that additionally includes the perturbation and the acceptance criteria. Furthermore, we propose three novel project-wise neighborhood operators. Our method is evaluated on benchmark instances proposed in the MISTA conference challenge and compared to the state-of-the-art approaches. Our algorithm obtains competitive results to the solver ranked third in the MISTA challenge. We also applied our method on the existing benchmark instances for multiple-mode resource constrained single project scheduling problems. We provide six new upper bounds for well-known instances of the MMLIB library.