Modeling duration choice in space–time multi-state supernetworks for individual activity-travel scheduling |
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Institution: | 1. School of Sustainable Engineering and the Built Environment, Arizona State University, USA;2. Department of Industrial & Systems Engineering, Institute for Sustainable Transportation & Logistics, University at Buffalo, USA;1. Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St. Stop C1761, Austin, TX 78712, USA\n;2. The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;1. Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 W. Taylor Street, Chicago, IL 60607-7023, USA;2. School of Civil and Environment Engineering, University of New South Wales, Sydney, NSW 2052, Australia |
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Abstract: | Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured. |
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Keywords: | Multi-state supernetwork Space–time Duration choice Activity-travel scheduling |
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