A meta-heuristic for capacitated green vehicle routing problem

The capacitated green vehicle routing problem is considered in this paper as a new variant of the vehicle routing problem. In this problem, alternative fuel-powered vehicles (AFVs) are used for distributing products. AFVs are assumed to have low fuel tank capacity. Therefore, during their distribution process, AFVs are required to visit alternative fuel stations (AFSs) for refueling. The design of the vehicle routes for AFVs becomes difficult due to the limited loading capacity, the low fuel tank capacity and the scarce availability of AFSs. Two solution methods, the two-phase heuristic algorithm and the meta-heuristic based on ant colony system, are proposed to solve the problem. The numerical experiment is performed on the randomly generated problem instances to evaluate the performance of the proposed algorithms.

[1]  Yuchun Xu,et al.  Development of a fuel consumption optimization model for the capacitated vehicle routing problem , 2012, Comput. Oper. Res..

[2]  Dominik Goeke,et al.  The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations , 2014, Transp. Sci..

[3]  Gilbert Laporte,et al.  The time-dependent pollution-routing problem , 2013 .

[4]  Robert L. McCormick,et al.  Operating Experience and Teardown Analysis for Engines Operated on Biodiesel Blends (B20) , 2005 .

[5]  Benjamín Barán,et al.  A Multiobjective Ant Colony System for Vehicle Routing Problem with Time Windows , 2003, Applied Informatics.

[6]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[7]  Gilbert Laporte,et al.  The multi-depot vehicle routing problem with inter-depot routes , 2007, Eur. J. Oper. Res..

[8]  Richard W. Eglese,et al.  Combinatorial optimization and Green Logistics , 2007 .

[9]  Gregory Gutin,et al.  Traveling salesman should not be greedy: domination analysis of greedy-type heuristics for the TSP , 2001, Discret. Appl. Math..

[10]  Moshe Dror,et al.  A branch and cut algorithm for the VRP with satellite facilities , 1998 .

[11]  Gilbert Laporte,et al.  An adaptive large neighborhood search heuristic for the Pollution-Routing Problem , 2012, Eur. J. Oper. Res..

[12]  Helman I. Stern,et al.  Vehicle fleet refueling strategies to maximize operational range , 1983 .

[13]  Yuvraj Gajpal,et al.  An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup , 2009, Comput. Oper. Res..

[14]  Tarek Y. ElMekkawy,et al.  Hybridized ant colony algorithm for the Multi Compartment Vehicle Routing Problem , 2015, Appl. Soft Comput..

[15]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[16]  Helman I. Stern,et al.  Optimal refueling strategies for a mixed-vehicle fleet , 1985 .

[17]  Gilbert Laporte,et al.  The fleet size and mix pollution-routing problem , 2014 .

[18]  Sai Ho Chung,et al.  Survey of Green Vehicle Routing Problem: Past and future trends , 2014, Expert Syst. Appl..

[19]  Giovanni Righini,et al.  A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges , 2014 .

[20]  Elise Miller-Hooks,et al.  A Green Vehicle Routing Problem , 2012 .

[21]  Emmanouil E. Zachariadis,et al.  A Hybrid Guided Local Search for the Vehicle-Routing Problem with Intermediate Replenishment Facilities , 2008, INFORMS J. Comput..

[22]  Yiyo Kuo,et al.  Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem , 2010, Comput. Ind. Eng..

[23]  Thomas Stützle,et al.  Ant Colony Optimization , 2009, EMO.

[24]  Qiang Meng,et al.  Distance-constrained capacitated vehicle routing problems with flexible assignment of start and end depots , 2008, Math. Comput. Model..

[25]  Patrick R. McMullen,et al.  Ant colony optimization techniques for the vehicle routing problem , 2004, Adv. Eng. Informatics.

[26]  Yuvraj Gajpal,et al.  Multi-ant colony system (MACS) for a vehicle routing problem with backhauls , 2009, Eur. J. Oper. Res..

[27]  Gilbert Laporte,et al.  The Pollution-Routing Problem , 2011 .