Proactive and reactive risk-aware project scheduling

In order to create a testbed for Computational Intelligence (CI) methods dealing with complex, non-deterministic and dynamic environments we propose a definition of a new class of problems, based on the real-world task of project scheduling and executing with risk management. Therefore, we define Risk-Aware Project Scheduling Problem (RAPSP) as a (significant) modification of the Resource-Constrained Project Scheduling Problem (RCPSP). We argue that this task is, considering its daunting complexity, sometimes surprisingly well solved by experienced humans, relying both on tools and their intuition. We speculate that a CI-based solver for RAPSP should also employ multiple cognitively-inspired approaches to the problem and we propose three such solvers of varying complexity and inspiration. Their efficacy comparison is in line with our expectations and supports our claims.