Decision Support System of Truck Routing and Refueling: A Dual-Objective Approach

The variable-route vehicle-refueling problem (VRVRP) is a variant of the network-flow problem which seeks, for a vehicle traveling from origin s to destination d, both the route and the refueling policy (sequence of fuel stations to use between s and d) that jointly minimize the fuel cost of operating the vehicle. Commercial-grade decision support systems that solve the VRVRP are widely used by motor carriers, but they provide heuristic solutions only. Exact methods are available from the academic side, but because they focus on minimizing costs, they tend to cut fuel costs in exchange for increased vehicle miles (which can increase fuel consumptions and pollutants emission). We propose a new approach to the VRVRP that allows carriers to jointly seek the two possibly conflicting goals; minimizing fuel cost and vehicle miles. Computational testing shows that our approach (i) outperforms the commercial software products in both goals, and (ii) finds solutions that require significantly less vehicle miles than those given by the exact method proposed in the academic literature, without incurring unacceptable increases in fuel cost.

[1]  Yoshinori Suzuki,et al.  A generic model of motor‐carrier fuel optimization , 2008 .

[2]  Leonard Evans,et al.  Automobile Fuel Economy on Fixed Urban Driving Schedules , 1978 .

[3]  Richard D. Wollmer,et al.  A Fuel Management Model for the Airline Industry , 1992, Oper. Res..

[4]  Yoshinori Suzuki,et al.  A new truck-routing approach for reducing fuel consumption and pollutants emission , 2011 .

[5]  Nate Gertsch,et al.  A linear-time algorithm for finding optimal vehicle refueling policies , 2007, Oper. Res. Lett..

[6]  Jasbir S. Arora,et al.  12 – Introduction to Optimum Design with MATLAB , 2004 .

[7]  Shieu-Hong Lin,et al.  Finding Optimal Refueling Policies in Transportation Networks , 2008, AAIM.

[8]  Yanfeng Ouyang,et al.  Optimal fueling strategies for locomotive fleets in railroad networks , 2010 .

[9]  F. Arcelus,et al.  Green logistics at Eroski: A case study , 2011 .

[10]  Yoshinori Suzuki A variable-reduction technique for the fixed-route vehicle-refueling problem , 2014, Comput. Ind. Eng..

[11]  Sergei Savin,et al.  Going Bunkers: The Joint Route Selection and Refueling Problem , 2009, Manuf. Serv. Oper. Manag..

[12]  Yoshinori Suzuki A decision support system of dynamic vehicle refueling , 2009, Decis. Support Syst..

[13]  Vedat Verter,et al.  A Tactical Planning Model for Railroad Transportation of Dangerous Goods , 2011, Transp. Sci..

[14]  Wlodzimierz Ogryczak,et al.  A Goal Programming model of the reference point method , 1994, Ann. Oper. Res..

[15]  Karin Brundell-Freij,et al.  Optimizing route choice for lowest fuel consumption - Potential effects of a new driver support tool , 2006 .

[16]  Srinivas Talluri,et al.  Multiproduct, Multicriteria Model for Supplier Selection with Product Life-Cycle Considerations , 2006, Decis. Sci..

[17]  Kanok Boriboonsomsin,et al.  Impacts of Road Grade on Fuel Consumption and Carbon Dioxide Emissions Evidenced by Use of Advanced Navigation Systems , 2009 .

[18]  Masatoshi Sakawa Fuzzy Multiobjective and Multilevel Optimization , 2003 .

[19]  Xiaoyan Zhu,et al.  Three-stage approaches for optimizing some variations of the resource constrained shortest-path sub-problem in a column generation context , 2007, Eur. J. Oper. Res..

[20]  Brian T. Denton,et al.  Bi‐Criteria Scheduling of Surgical Services for an Outpatient Procedure Center , 2011 .