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A Parallel Multi-Start NSGA II Algorithm for Multiobjective Energy Reduction Vehicle Routing Problem

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Evolutionary Multi-Criterion Optimization (EMO 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9018))

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Abstract

The Multiobjective Energy Reduction Vehicle Routing Problem is a variant of the classic Vehicle Routing Problem where simultaneous optimization of more than one objective functions is required. In this paper, the problem is formulated with three different competitive objective functions. The first objective function corresponds to the optimization of the time needed for the vehicle to travel between two customers or between the customer and the depot, the second objective function is the minimization of the distance and the fuel consumption when a delivery route is planned and the third objective function is the minimization of the distance and the fuel consumption when a pickup route is planned. The problem is solved with a modified version of the NSGA II, with a use of more than one population, a multi start method for the creation of the initial population and a Variable Neighborhood Search algorithm for the improvement of the solution of each individual separately. In order to give the quality of the methodology, experiments are conducted using appropriately modified for the Vehicle Routing Problem instances based on the classic Euclidean Traveling Salesman Problem benchmark instances taken from the TSP library.

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References

  1. Chand, P., Mohanty, J.R.: Multi objective genetic approach for solving vehicle routing problem. International Journal of Computer Theory and Engineering 5(6), 846–849 (2013)

    Article  Google Scholar 

  2. Christofides, N., Mingozzi, A., Toth, P.: The vehicle routing problem. In: Christofides, N., Mingozzi, A., Toth, P., Sandi, C. (Eds.) Combinatorial Optimization. Wiley, Chichester (1979)

    Google Scholar 

  3. Coello Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-Objective Problems. Springer (2007)

    Google Scholar 

  4. Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Deb, K., Rudolph, G., Lutton, E., Merelo, J.J., Schoenauer, M., Schwefel, H.-P., Yao, X. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 849–858. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  5. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)

    Article  Google Scholar 

  6. Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedure. Journal of Global Optimization 6, 109–133 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  7. Gutin, G., Punnen, A.P.: The Traveling Salesman Problem and its Variations. Kluwer Academic Publishers, Dordrecht (2002)

    MATH  Google Scholar 

  8. Hansen, P., Mladenovic, N.: Variable neighborhood search: Principles and applications. European Journal of Operational Research 130, 449–467 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  9. Huayu, X., Wenhui, F., Tian, W., Lijun, Y.: An Or-opt NSGA-II algorithm for multi-objective vehicle routing problem with time windows. In: 4th IEEE Conference on Automation Science and Engineering, 309–314 (2008)

    Google Scholar 

  10. Jemai, J., Zekri, M., Mellouli, K.: An NSGA-II Algorithm for the Green Vehicle Routing Problem. In: Hao, J.-K., Middendorf, M. (eds.) EvoCOP 2012. LNCS, vol. 7245, pp. 37–48. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  11. Johnson, D.S., Papadimitriou, C.H.: Computational complexity. In: Lawer, E.L., Lenstra, J.K., Rinnoy Kan, A.H.D., Shmoys, D.B., (Eds.) The traveling salesman problem: a guided tour of combinatorial optimization. Wiley and Sons, 37–85 (1985)

    Google Scholar 

  12. Jozefowiez, N., Semet, F., Talbi, E.-G.: Enhancements of NSGA II and Its Application to the Vehicle Routing Problem with Route Balancing. In: Talbi, E.-G., Liardet, P., Collet, P., Lutton, E., Schoenauer, M. (eds.) EA 2005. LNCS, vol. 3871, pp. 131–142. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. Jozefowiez, N., Semet, F., Talbi, E.G.: Multi-objective vehicle routing problems. European Journal of Operational Research 189, 293–309 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  14. Laporte, G.: The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research 59, 345–358 (1992)

    Article  MATH  Google Scholar 

  15. Lawer, E.L., Lenstra, J.K., Rinnoy Kan, A.H.G.R., Shmoys, D.B.: The Traveling Salesman Problem: a guided tour of combinatorial optimization. Wiley and Sons (1985)

    Google Scholar 

  16. Lichtblau, D.: Discrete optimization using Mathematica. In: Callaos, N., Ebisuzaki, T., Starr, B., Abe, J.M., Lichtblau, D. (Eds.) World multi-conference on systemics, cybernetics and informatics (SCI 2002), International Institute of Informatics and Systemics, 16, 169–174 (2002)

    Google Scholar 

  17. Lin, S.: Computer solutions of the traveling salesman problem. Bell Systems Technical Journal 44(10), 2245–2269 (1965)

    Article  MATH  Google Scholar 

  18. Ombuki, B., Ross, B.J., Hanshar, F.: Multi-objective genetic algorithms for vehicle routing problem with time windows. Applied Intelligence 24, 17–30 (2006)

    Article  Google Scholar 

  19. Sarker, R., Coello Coello, C.A.: Assessment methodologies for multiobjective evolutionary algorithms. Evolutionary Optimization, International Series in Operations Research and Management Science 48, 177–195 (2002)

    MathSciNet  Google Scholar 

  20. Toth, P., Vigo, D.: The Vehicle Routing Problem. Monographs on Discrete Mathematics and Applications, Siam (2002)

    Book  MATH  Google Scholar 

  21. Xiao, Y., Zhao, Q., Kaku, I., Xu, Y.: Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Computers and Operations Research 39(7), 1419–1431 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  22. Zitzler, E., Deb, K., Thiele, L.: Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation 8(2), 173–195 (2000)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Production Engineering and Management, Technical University of Crete, Chania, Greece

    Iraklis-Dimitrios Psychas, Magdalene Marinaki & Yannis Marinakis

Authors
  1. Iraklis-Dimitrios Psychas
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  2. Magdalene Marinaki
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  3. Yannis Marinakis
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Correspondence to Yannis Marinakis .

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Editors and Affiliations

  1. Institute for Polymers and Composites/I3N,University of Minho, Guimaraes, Portugal

    António Gaspar-Cunha

  2. Dept. of Electrical and Computer Engg, University of Coimbra, Coimbra, Portugal

    Carlos Henggeler Antunes

  3. CINVESTAV-IPN Depto. de Computacíon, Col. San Pedro Zacatenco, México DF, Mexico

    Carlos Coello Coello

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Psychas, ID., Marinaki, M., Marinakis, Y. (2015). A Parallel Multi-Start NSGA II Algorithm for Multiobjective Energy Reduction Vehicle Routing Problem. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C. (eds) Evolutionary Multi-Criterion Optimization. EMO 2015. Lecture Notes in Computer Science(), vol 9018. Springer, Cham. https://doi.org/10.1007/978-3-319-15934-8_23

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  • DOI: https://doi.org/10.1007/978-3-319-15934-8_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15933-1

  • Online ISBN: 978-3-319-15934-8

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