Demand Responsive Feeder Transit Scheduling with Flexible Service Quality

Demand responsive feeder transit is a transportation mode providing transportation service between travel destinations or origins and hub stations. In order to exploit the flexibility of the demand responsive feeder transit system while maintaining its economy, this paper introduces travel freedom of requests in terms of range of service quality of potential trip predefined by requests while reserving the transportation service as part of the constraints to the demand responsive feeder transit systems. The reserved service quality includes the range of satisfactory and acceptable qualities, where transportation service with acceptable quality is only accepted with certain discount. The service quality is represented as a metric called detour coefficient, which is the proportion of the trip time according to the vehicle schedules to the direct driving time between the travel origin and destination of a request. An optimization model for scheduling the proposed system is formulated followed by the development of a customized simulated annealing solution approach based on the characteristics of the proposed problem. The solution method is verified and validated through computational experiment on a randomly generated instance.

[1]  Zhen Yang,et al.  Hybrid simulated annealing and reduced variable neighbourhood search for an aircraft scheduling and parking problem , 2020, Int. J. Prod. Res..

[2]  Chengbin Chu,et al.  A fast heuristic for solving a large-scale static dial-a-ride problem under complex constraints , 2006, Eur. J. Oper. Res..

[3]  R. W. Calvo,et al.  A Granular Tabu Search algorithm for the Dial-a-Ride Problem , 2013 .

[4]  Ali Haghani,et al.  A methodology for choosing between fixed‐route and flex‐route policies for transit services , 2015 .

[5]  Eric J. Gonzales,et al.  Demand responsive transit systems with time-dependent demand: User equilibrium, system optimum, and management strategy , 2016 .

[6]  Paolo Detti,et al.  A multi-depot dial-a-ride problem with heterogeneous vehicles and compatibility constraints in healthcare☆ , 2017 .

[7]  Gilbert Laporte,et al.  Measuring quality of service in dial-a-ride operations: the case of a Canadian city , 2012 .

[8]  Hasan Hüseyin Turan,et al.  A multi-skilled workforce optimisation in maintenance logistics networks by multi-thread simulated annealing algorithms , 2020, Int. J. Prod. Res..

[9]  Hokey Min Evaluating the service quality of para-transit systems: an exploratory study of the Toledo area regional transit authority , 2011 .

[10]  Gintaras Palubeckis,et al.  Hybridizing simulated annealing with variable neighborhood search for bipartite graph crossing minimization , 2019, Appl. Math. Comput..

[11]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[12]  Richard F. Hartl,et al.  Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem , 2014, Eur. J. Oper. Res..

[13]  Xiugang Li,et al.  Feeder transit services: Choosing between fixed and demand responsive policy , 2010 .

[14]  Xuesong Zhou,et al.  Customized bus service design for jointly optimizing passenger-to-vehicle assignment and vehicle routing , 2017 .

[15]  R M Jorgensen,et al.  Solving the Dial-a-Ride problem using genetic algorithms , 2007, J. Oper. Res. Soc..