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Integrating bus services with mixed fleets
Affiliation:1. Department of Finance and Investment, Sun Yat-Sen University, Bldg 388, 135 Xingangxi Rd, Guangzhou 510275, China;2. Department of Civil and Urban Engineering, New York University, 6 Metro Tech Center, Brooklyn, NY 11201, USA;3. Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742, USA;1. University of California, Berkeley, CA 94707, United States;2. University of Illinois, Urbana-Champaign, IL 61820, United States
Abstract:Conventional bus service (with fixed routes and schedules) has lower average cost than flexible bus service (with demand-responsive routes) at high demand densities. At low demand densities flexible bus service has lower average costs and provides convenient door-to-door service. Bus size and operation type are related since larger buses have lower average cost per passenger at higher demand densities. The operation type and other decisions are jointly optimized here for a bus transit system connecting a major terminal to local regions. Conventional and flexible bus sizes, conventional bus route spacings, areas of service zones for flexible buses, headways, and fleet sizes are jointly optimized in multi-dimensional nonlinear mixed integer optimization problems. To solve them, we propose a hybrid approach, which combines analytic optimization with a Genetic Algorithm. Numerical analysis confirms that the proposed method provides near-optimal solutions and shows how the proposed Mixed Fleet Variable Type Bus Operation (MFV) can reduce total cost compared to alternative operations such as Single Fleet Conventional Bus (SFC), Single Fleet Flexible Bus (SFF), Mixed Fleet Conventional Bus (MFC) and Mixed Fleet Flexible Bus (MFF). With consistent system-wide bus sizes, capital costs are reduced by sharing fleets over times and over regions. The sensitivity of results to several important parameters is also explored.
Keywords:Public transportation  Conventional bus  Flexible bus  Genetic algorithm  Analytic optimization  Hybrid approach
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