Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 689-716.

Route planning and goods distribution are a major component of any logistics. Vehicle Routing Problem is a class of problems addressing the issues of logistics. Vehicle Routing Problem with Limited Refueling Halts is introduced in this paper. The objective is to plan a route with an emphasis on the time and cost involved in refueling vehicles. The method is tailored to find optimal routes with minimal halts at the refueling stations. The problem is modeled as a bi objective optimization problem and is solved using particle swarm optimization. A new mutation operator called greedy mutation operator is introduced. Experiments are conducted with available data sets and MATLABR2011a is used for implementation.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2014064
Classification : 90B06, 90C27, 90C59
Mots-clés : Logistics, Vehicle Routing Problem, particle swarm optimization
Poonthalir, Ganesan 1 ; Nadarajan, Rethnaswamy 1 ; Geetha, Shanmugam 2

1 Department of Applied Mathematics and Computational Sciences, PSG College of Technology, 641004 Coimbatore, India.
2 Department of Computer Applications, PSG College of Technology, 641004 Coimbatore, India.
@article{RO_2015__49_4_689_0,
     author = {Poonthalir, Ganesan and Nadarajan, Rethnaswamy and Geetha, Shanmugam},
     title = {Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {689--716},
     publisher = {EDP-Sciences},
     volume = {49},
     number = {4},
     year = {2015},
     doi = {10.1051/ro/2014064},
     zbl = {1322.90011},
     language = {en},
     url = {http://www.numdam.org/articles/10.1051/ro/2014064/}
}
TY  - JOUR
AU  - Poonthalir, Ganesan
AU  - Nadarajan, Rethnaswamy
AU  - Geetha, Shanmugam
TI  - Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator
JO  - RAIRO - Operations Research - Recherche Opérationnelle
PY  - 2015
SP  - 689
EP  - 716
VL  - 49
IS  - 4
PB  - EDP-Sciences
UR  - http://www.numdam.org/articles/10.1051/ro/2014064/
DO  - 10.1051/ro/2014064
LA  - en
ID  - RO_2015__49_4_689_0
ER  - 
%0 Journal Article
%A Poonthalir, Ganesan
%A Nadarajan, Rethnaswamy
%A Geetha, Shanmugam
%T Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator
%J RAIRO - Operations Research - Recherche Opérationnelle
%D 2015
%P 689-716
%V 49
%N 4
%I EDP-Sciences
%U http://www.numdam.org/articles/10.1051/ro/2014064/
%R 10.1051/ro/2014064
%G en
%F RO_2015__49_4_689_0
Poonthalir, Ganesan; Nadarajan, Rethnaswamy; Geetha, Shanmugam. Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 689-716. doi : 10.1051/ro/2014064. http://www.numdam.org/articles/10.1051/ro/2014064/

S. Agarwal, B.K. Panigrahi and M.K. Tiwari, Multi objective particle swarm algorithm with fuzzy clustering for electrical power dispatch. IEEE Trans. Evol. Comput. 12 (2008) 529–541. | DOI

A. Artmeier, J. Haselmayr, M. Leucker and M. Sachenbacher, The shortest path problem revisited: Optimal routing for electric vehicles, in Advances in Artificial Intelligence. Springer, Berlin, Heidelberg (2010) 309–316.

S. Aviral, P. Joseph and V. Venkatasubramanian, An optimization framework for cost effective design of refueling station infrastructure for alternative fuel vehicles. Comput. Chem. Eng. 35 (2011) 1431–1438. | DOI

T. Bektas and G. Laporte, The pollution-routing problem. Transp. Res. Part B 45 (2011) 1232–1250. | DOI

M. Caramia and P. Dell’Olmo, Multi-objective management in freight logistics. Springer (2008).

V. Chankong and Y.Y. Haimes, Multiobjective decision making: theory and methodology. Elsevier Science, New York (1983). | Zbl

C.A.C. Coello and M.S. Lechuga, MOPSO: A proposal for multiple objective particle swarm optimization, in Proc. of 2002 Congress on Evolutionary Computation part of the 2002 IEEE World Congress on Computational Intelligence. IEEE Press, Hawaii (2002) 1051–1056.

C.A.C. Coello and G.T. Pulido, Lechuga MSHandling multiple objectives with particle swarm optimization. IEEE Trans. Evol. Comput. (2004) 8 256–279. | DOI

J.L. Cohon, Multiobjective Programming and Planning. Academic Press, New York (1978). | Zbl

S. Erdogan and E. Miller-Hooks, A green vehicle routing problem. Transp. Res. Part E 48 (2012) 100–114. | DOI

M. Gendreau, G. Laporte and J.Y. Potvin, Metaheuristics for the vehicle routing problem, Technical Report CRT-963. Centre de Recherche sur les Transports, Université de Montréal (1999).

B.L. Golden and A.A. Assad, Vehicle routing: methods and studies. North-Holland, Amsterdam (1988). | Zbl

W. Han, P. Yang, H. Ren and J. Sun, Comparison study of several kinds of inertia weight for PSO, in Proc. of IEEE international conference on progress in informatics and computing. IEEE Comput. Soc. (2010) 280–284.

V.L. Huang, P.N. Suganthan and J.J. Liang, Comprehensive learning particle swarm optimizer for solving multi objective optimization problems. Int. J. Intell. Syst. 21 (2006) 209–226. | DOI | Zbl

C.L. Hwang, A.S.M. Masud, S.R. Paidy and K.P. Yoon, Multiple Objective Decision Making, Methods and Applications: a State of the Art Survey, Lecture Notes in Economics and Mathematical Systems, 164. Springer-Verlag, Berlin (1979). | Zbl

J. Kennedy and R.C. Eberhart, Swarm Intelligence. Morgan Kaufmann, San Francisco (2001).

Y. Kuo, Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Comput. Ind. Eng. 59 (2010) 157–165. | DOI

G. Laporte and I.H. Osman, Routing problems: a bibliography. Ann. Oper. Res. 61 (1995) 227–262. | DOI | Zbl

D. Levy, K. Sundar and S. Rathinam, Heuristics for routing heterogenous unmanned vehicles with fuel constraints. Math. Problems Eng. (2014), DOI:. | DOI

G. Mavrotas, Effective implementation of the ε constraint method in Multi-Objective Mathematical Programming problems. Appl. Math. Comput. 213 (2009) 455–465. | Zbl

A.A. Mousa, M.A. El-Shorbagy and W.F. Abd-El-Wahed, Local search based hybrid particle swarm optimization algorithm for multi objective optimization. Swarm Evol. Comput. 3 (2012) 1–14. | DOI

E. Ozcan and C. Mohan, Particle swarm optimisation: Surfing the waves, in Proc. of IEEE international congress on evolutionary computation. IEEE Computer Society (1999) 1939–1944.

V. Pareto, Manuale di economica politica, societa editrice Libraria, Milan, Translated into English by A.S. Schwier, as Manual of political economy, edited by A.S. Schwier and A.N. Page, A.M. Kelly. New York (1971).

K.E. Parsopoulos and M.N. Vrahatis, Particle swarm optimization method in multi objective problems, in Proc. of 2002 ACM Symposium on Applied Computing (2002) 603–607.

K.E. Parsopoulos, M.N.Vrahatis, in Multiobjective particle swarm optimization approaches, multi-objective optimization in computational intelligence: Theory and practice, by Lam Thu Bui, Sameer Alam (Eds.), Chapter 2, pp. 20–42. IGI Global (2008).

D. Pisinger and S. Ropke, A general heuristic for Vehicle routing problem. Department of Computer Science, University of Copenhagen (2005). | Zbl

A. Sbihi and R.W. Eglese, Combinatorial optimization and green logistics. 4OR-Q J. Oper. Res. 5 (2007) 99–116. | DOI | Zbl

P. Toth and D. Vigo, An overview of vehicle routing problems, in The vehicle routing problem. edited by P. Toth and D. Vigo. SIAM monographs on discrete mathematics and applications (2002) 1–26. | Zbl

P.K. Tripathi, S. Bandhopadhyay and S.K. Pal, Multi objective particle swarm optimization with time variant inertia and acceleration coefficients. Inform. Sci. 177 (2007) 5033–5049. | DOI | Zbl

Y.W. Wang and C.R. Wang Locating passenger vehicle refueling stations. Transp. Res. E 46 (2010) 791–801. | DOI

Y. Xiao, Q. Zhao, I. Kaku and Y. Xu, Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Comput. Oper. Res. 39 (2012) 1419–1431. | DOI | Zbl

L. Zadeh, Optimality and non-scalar-valued performance criteria. IEEE Trans. Autom. Control 8 (1963) 59–60. | DOI

Cité par Sources :