Benefits of horizontal cooperation in dial-a-ride services

Dial-a-ride services provide collective on-demand transportation, usually tailored to the needs of people with reduced mobility. This paper investigates the operational effects of horizontal cooperation among dial-a-ride providers. The current practice is that users choose a particular provider to submit their requests. Providers operating in the same area create their routing solutions independently of each other, given their own set of customers. In contrast, horizontal cooperation through joint route planning implies that customer requests can be exchanged among providers in order to minimize the overall routing cost. In addition to quantifying the operational benefits generated by such a horizontal cooperation, this paper identifies operational characteristics that influence the magnitude of the savings. A real-life case study reveals the reasons why providers benefit from certain request exchanges, as well as the extent to which these exchanges are predictable in advance. The solutions are obtained using a large neighborhood search algorithm that performs well on benchmark data.

[1]  Fabien Lehuédé,et al.  The Dial-A-Ride Problem with Transfers , 2014, Comput. Oper. Res..

[2]  Verena Schmid,et al.  Hybrid column generation and large neighborhood search for the dial-a-ride problem , 2013, Comput. Oper. Res..

[3]  Marc Salomon,et al.  Joint Route Planning Under Varying Market Conditions , 2006 .

[4]  Kris Braekers,et al.  Multi-directional local search for a bi-objective dial-a-ride problem in patient transportation , 2017, Comput. Oper. Res..

[5]  Gilbert Laporte,et al.  Quality of service in dial-a-ride operations , 2009, Comput. Ind. Eng..

[6]  Jonathan F. Bard,et al.  The heterogeneous pickup and delivery problem with configurable vehicle capacity , 2013 .

[7]  Gilbert Laporte,et al.  Dynamic pickup and delivery problems , 2010, Eur. J. Oper. Res..

[8]  Gerrit K. Janssens,et al.  Analysis of collaborative savings and cost allocation techniques for the cooperative carrier facility location problem , 2016, J. Oper. Res. Soc..

[9]  David Pisinger,et al.  An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows , 2006, Transp. Sci..

[10]  Sophie N. Parragh Introducing heterogeneous users and vehicles into models and algorithms for the dial-a-ride problem , 2011, Transportation research. Part C, Emerging technologies.

[11]  David Pisinger,et al.  Large Neighborhood Search , 2018, Handbook of Metaheuristics.

[12]  Gilbert Laporte,et al.  Models and branch-and-cut algorithms for pickup and delivery problems with time windows , 2007 .

[13]  Richard F. Hartl,et al.  Variable neighborhood search for the dial-a-ride problem , 2010, Comput. Oper. Res..

[14]  S. Tijs,et al.  Game theory and cost allocation problems , 1986 .

[15]  Philippe Lacomme,et al.  An ELS-based approach with dynamic probabilities management in local search for the Dial-A-Ride Problem , 2016, Eng. Appl. Artif. Intell..

[16]  Kris Braekers,et al.  Typology and literature review for dial-a-ride problems , 2017, Ann. Oper. Res..

[17]  Gilbert Laporte,et al.  Horizontal cooperation among freight carriers: request allocation and profit sharing , 2008, J. Oper. Res. Soc..

[18]  Éric D. Taillard,et al.  Parallel iterative search methods for vehicle routing problems , 1993, Networks.

[19]  Leslie Pérez Cáceres,et al.  The irace package: Iterated racing for automatic algorithm configuration , 2016 .

[20]  Stefan Irnich,et al.  Effective Handling of Dynamic Time Windows and Its Application to Solving the Dial-a-Ride Problem , 2015, Transp. Sci..

[21]  G. Laporte,et al.  A tabu search heuristic for periodic and multi-depot vehicle routing problems , 1997, Networks.

[22]  Kris Braekers,et al.  Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem , 2016 .

[23]  Gilbert Laporte,et al.  A Tabu Search Heuristic for the Static Multi-Vehicle Dial-a-Ride Problem , 2002 .

[24]  Jean-François Cordeau,et al.  A Branch-and-Cut Algorithm for the Dial-a-Ride Problem , 2006, Oper. Res..

[25]  Richard F. Hartl,et al.  A survey on pickup and delivery problems , 2008 .

[26]  Kris Braekers,et al.  Operational effects of service level variations for the dial-a-ride problem , 2017, Central Eur. J. Oper. Res..

[27]  Robert B. Dial Autonomous Dial-a-Ride Transit: Software Functionality and Architecture Overview , 2002 .

[28]  Chengbin Chu,et al.  The study of a dynamic dial-a-ride problem under time-dependent and stochastic environments , 2008, Eur. J. Oper. Res..

[29]  W. Dullaert,et al.  Horizontal cooperation in logistics : Opportunities and impediments , 2007 .

[30]  Gerrit K. Janssens,et al.  Collaborative Logistics from the Perspective of Road Transportation Companies , 2013 .

[31]  Kris Braekers,et al.  A hybrid Genetic Algorithm for the Heterogeneous Dial-A-Ride Problem , 2017, Comput. Oper. Res..

[32]  Pieter Leyman,et al.  Termination criteria for metaheuristics: Is computation time worth the time? , 2017 .

[33]  Fabien Lehuédé,et al.  A multi-criteria large neighbourhood search for the transportation of disabled people , 2014, J. Oper. Res. Soc..

[34]  Gerrit K. Janssens,et al.  Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots , 2014 .

[35]  G. Dueck New optimization heuristics , 1993 .

[36]  Ron S. Kenett,et al.  Statistics for Business and Economics. , 1988 .