An iterative dynamic programming method for activity location allocation reduces the discrepancy between simulated travel times and survey-reported times by 52.2% on dummy data.
Zooming into mobility to understand cities: A review of mobility-driven urban studies
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Generating Realistic Individual Activity Schedules via Activity Location Allocation Based on Simulated Travel Times
An iterative dynamic programming method for activity location allocation reduces the discrepancy between simulated travel times and survey-reported times by 52.2% on dummy data.