New approaches to generating comprehensive all-day activity-travel schedules

Activity-based travel demand models derive travel demand from people’s desire to pursue ac-tivities in time and space. They generate activity-travel schedules for individual travellers orhomogeneous groups of travellers. Comprehensive activity-travel schedules hold informationon which activities are performed, in which order, where and for how long, and which travelmodes are used between the activities including corresponding routes. This paper presentsPlanomatX, a new scheduling algorithm based on Tabu Search that generates comprehen-sively optimized all-day schedules. The paper furthermore presents a new concept of sched-ule recycling that significantly reduces simulation runtimes by re-using schedules of opti-mized travellers for other non-optimized travellers. Both PlanomatX and schedule recyclingare part of the agent-based microsimulation MATSim (Multi-Agent Transport Simulation,http://matsim.org). MATSim’s utility function has been adapted to cope with the enhancedfunctionality of PlanomatX and schedule recycling. First test results on the greater Zurich sce-nario with more than 170,000 agents show that PlanomatX achieves significantly better op-timization results than MATSim’s existing scheduling algorithms. However, it also leads todisproportional simulation runtimes. Schedule recycling relieves this drawback and allows forgenerating comprehensively optimized all-day schedules for large-scale scenarios at affordableruntimes.