NSGA-II optimization of resource-level handover policies cuts cost by 37% and waiting time by 58% on average across synthetic and real event logs
The work introduces the first approach for multi-objective optimization of resource-level handover policies in business processes: taking a Multi-Agent System (MAS) simulation model as input, it uses NSGA-II to search for Pareto-optimal person-specific handover policies, and across five synthetic Loan Application variants and seven real event logs it reduces cost by an average of 37% and waiting time by 58% relative to the as-is process, outperforming availability, random, lowest-cost (LC), and shortest-processing-time (SPT) heuristic baselines in most settings.