Abstract
In this paper we deal with a variant of the VRPTW that is oriented to the quality of service to customers. In this model, we incorporate a measure of quality associated with the time the vehicles reach customers within their time window as an objective. We apply a bi-objective discrete PSO to deal with the problem. The procedure performance is analyzed on classical and real data based instances.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ai J, Kachitvichyanukul V (2009) A particle swarm optimisation for vehicle routing problem with time windows. Int J Oper Res 6(4):519–537
Ai TJ, Kachitvichyanukul V (2009) Particle swarm optimization and two solution representations for solving the capacitated vehicle routing problem. Comput Ind Eng 56(1):380–387
Ai TJ, Kachitvichyanukul V (2009) A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Comput Oper Res 36:1693–1702
Al-kazemi B, Mohan CK (2000) Multi-phase discrete particle swarm optimization. In: FEA 2000: 4th international workshop on frontiers in evolutionary algorithms
Banks A, Vincent J, Anyakoha C (2008) A review of particle swarm optimization. part ii: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications. Nat Comput 7:109–124
Castro J, Landa-Silva D, Perez J (2009) Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach. In: Krasnogor N, Melin-Batista M, Prez J, Moreno-Vega J, Pelta D (eds) Nature inspired cooperative strategies for optimization (NICSO 2008), vol 236. Studies in computational intelligence. Springer, Berlin, pp 103–114
Castro-Gutierrez J, Landa-Silva D, Moreno JA (2011) Nature of real-world multi-objective vehicle routing with evolutionary algorithms. In: Proceedings of the 2011 IEEE international conference on systems, man, and cybernetics (IEEE SMC 2011), IEEE Press, pp 257–264
Chang R, Lu C (2002) Feeder reconfiguration for load factor improvement. In: Power engineering society winter meeting, 2002, vol 2, pp 980–984. IEEE. doi:10.1109/PESW.2002.985152
Chen Al, Yang Gk, Wu Zm (2006) Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem. J Zhejiang Univ-Sci A 7(4): 607–614. doi:10.1631/jzus.2006.A0607
Chen P, Dong X, Niu Y (2012) An iterated local search algorithm for the cumulative capacitated vehicle routing problem. In: Tan H (ed) Technology for education and learning, vol 136, Advances in intelligent systems and computing. Springer, Berlin, pp 575–581
Coello CC, Lechuga GPMS (2004) Handling multiple objectives with particle swarm optimization. IEEE Tran Evol Comput 8(3):256–279
Consoli S, Moreno-Perez J, Darby-Dowman K, Mladenovic N (2010) Discrete particle swarm optimization for the minimum labelling steiner tree problem. Nat Comput 9(1):29–46
Consoli S, Perez JM, Darby-Dowman K, Mladenovic N (2008) Discrete particle swarm optimization for the minimum labelling steiner tree problem. In: Krasnogor N, Nicosia G, Pavone M, Pelta D (eds) Nature inspired cooperative strategies for optimization (NICSO 2007), vol 129. Studies in computational intelligence. Springer, Berlin, pp 313–322
Corberan A, Fernndez E, Laguna M (2002) Heuristic solutions to the problem of routing school buses with multiple objectives. J Oper Res Soc 53(4), 427–435. doi:10.1057/palgrave.jors.2601324
Eberhart RC, Shi Y (2001) Particle swarm optimization: developments, applications and resources. In: IEEE (ed) proceeding congress on evolutionary computation, vol 1, pp 81–86
Gomez-Gonzalez M, Lopez A, Jurado F (2013) Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system. Energy conversion and management 65:539–545. doi:10.1016/j.enconman.2012.07.029
Gong YJ, Zhang J, Liu O, Huang RZ, Chung HSH, Shi YH (2012) Optimizing the vehicle routing problem with time windows: a discrete particle swarm optimization approach. IEEE Trans Syst Man Cybern Part C: Appl Rev 42(2):254–267
Jin-Kao H, Galinier P, Habib M (2000) Métaheuristiques pour l’optimisation combinatoire et l’affectation sous contraintes. Revue d’Intelligence Artificielle 13(2):283–324
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, vol 4, pp 1942–1948
Kennedy J, Eberhart R (1997) A discrete binary version of the particle swarm algorithm. In: IEEE international conference on systems, man and Cybernetics 1997. Computational cybernetics and simulation 1997, vol 5, pp 4104–4108. doi:10.1109/ICSMC.1997.637339
Kennedy J, Eberhart R (2001) Swarm intelligence. Morgan Kaufmann Publishers, San Francisco
Li J (2011) Study of a multi-objective vehicle routing problem with time window based on particle swarm optimization. In: 3rd international workshop on intelligent systems and applications (ISA) 2011, pp 1–4
Lin CT (2008) Using predicting particle swarm optimization to solve the vehicle routing problem with time windows. In: IEEE international conference on industrial engineering and engineering management (IEEM) 2008, pp 810–814
Liu X, Jiang W, Xie J (2009) Vehicle routing problem with time windows: a hybrid particle swarm optimization approach. In: 5th international conference on natural computation (ICNC) 2009, vol 4, pp 502–506
Mao Y, Deng Y (2010) Solving vehicle routing problem with time windows with hybrid evolutionary algorithm. In: 2nd WRI global congress on intelligent systems (GCIS) 2010, vol 1, pp 335–339
Marinakis Y, Marinaki M, Dounias G (2010) A hybrid particle swarm optimization algorithm for the vehicle routing problem. Eng Appl Artif Intell 23(4):463–472
Martinez FJ, Moreno JA (2008) Jumping frogs optimization: a new swarm method for discrete optimization. Technical Report 3, DEIOC. Universidad de La Laguna
Mohan CK, Al-kazemi BA (2001) Discrete particle swarm optimization. In: Proceedings of the workshop particle swarm optimization
Moreno-Perez J, Castro-Gutierrez J, Martinez-Garcia F, Melian B, Moreno-Vega J, Ramos J (2007) Discrete particle swarm optimization for the p-median problem. In: Proceedings of the 7th metaheuristics international conference. Montreal, Canada
Muoz-Zavala A, Hernndez-Aguirre A, Villa-Diharce E (2009) Particle evolutionary swarm multi-objective optimization for vehicle routing problem with time windows. In: Coello C, Dehuri S, Ghosh S (eds) Swarm intelligence for multi-objective problems in data mining, Studies in computational intelligence, vol 242, pp 233–257. Springer, Berlin
Ngueveu SU, Prins C, Wolfler-Calvo R (2010) An effective memetic algorithm for the cumulative capacitated vehicle routing problem. Comput Oper Res 37(11):1877–1885. doi:10.1016/j.cor.2009.06.014
Pampara G, Franken N, Engelbrecht A (2005) Combining particle swarm optimisation with angle modulation to solve binary problems. In: The 2005 IEEE congress on evolutionary computation, vol 1, pp 89–96. doi:10.1109/CEC.2005.1554671
Pengxin D, Shurong Z, Hongwei Z (2012) Improved particle swarm algorithm and its application in vehicle routing problem. In: Wu Y (ed) Software engineering and knowledge engineering: theory and practice, vol 114. Advances in intelligent and soft computing. Springer, Berlin, pp 269–274
Poli R (2008) Analysis of the publications on the applications of particle swarm optimisation. J Artif Evol App 2008:4:1–4:10. doi:10.1155/2008/685175
Potvin JY (2009) A review of bio-inspired algorithms for vehicle routing. In: Pereira F, Tavares J (eds) Bio-inspired algorithms for the vehicle routing problem, vol 161. Studies in computational intelligence. Springer, Berlin, pp 1–34
Reyes-Sierra M, Coello CAC (2006) Multi-objective particle swarm optimizers: a survey of the state-of-the-art. Int J Comput Intell Res 2(3):287–308
Seren C (2011) A hybrid jumping particle swarm optimization method for high dimensional unconstrained discrete problems. In: 2011 IEEE congress on evolutionary computation (CEC), pp 1649–1656. doi:10.1109/CEC.2011.5949813
Sun H, Wu B, Zhao YW, Wang W, Ma YL, Wang W (2004) Materials science forum. In: Ai X, Li J, Huang C (eds) Particle swarm optimization for vehicle routing problem with time windows (chap.), vol 471, pp 801–805
Toth P, Vigo D (eds) (2002) The vehicle routing problem, Monographs on discrete mathematics and applications, Society for industrial and applied mathematics publishing, vol 9
Wang H, Liu Y, Wu Z, Sun H, Zeng S, Kang L (2008) An improved particle swarm optimization with adaptive jumps. In: IEEE congress on evolutionary computation (CEC) 2008 (IEEE world congress on computational intelligence), pp 392–397. doi:10.1109/CEC.2008.4630827
Wang W, Wu B, Zhao YD, Feng P (2006) Particle swarm optimization for open vehicle routing problem. In: Huang DS, Li K, Irwing GW (eds) 2006 International conference on intelligen computing: part II (ICIC‘06), Springer, Berlin, pp 999–1007
Wang Z, Li J, Fan J, Fan C (2010) Research on improved hybrid particle swarm optimization for vehicle routing problem with time windows. In: 2010 International conference on artificial intelligence and computational intelligence (AICI), vol 1, pp 179–183
Yang S, Wang M, Jiao L (2004) A quantum particle swarm optimization. In: Congress on evolutionary computation CEC2004, vol 1, pp 320–324. doi:10.1109/CEC.2004.1330874
Zhen T, Zhu Y, Zhang Q (2009) A particle swarm optimization algorithm for the open vehicle routing problem. In: International conference on environmental science and information application technology ESIAT 2009, vol 2, pp 560–563
Zhu Q, Qian L, Li Y, Zhu S (2006) An improved particle swarm optimization algorithm for vehicle routing problem with time windows. In: IEEE congress on evolutionary computation CEC 2006, pp 1386–1390
Zou S, Ding PX, Zhang HW (2011) The improvement of hybrid particle swarm algorithm and its application. Adv Mater Res 268:798–802
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Brito, J., Expósito, A., Moreno-Pérez, J.A. (2015). Bi-objective Discrete PSO for Service-Oriented VRPTW. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-11541-2_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-11541-2_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11540-5
Online ISBN: 978-3-319-11541-2
eBook Packages: EngineeringEngineering (R0)