| Peer-Reviewed

A Bi-objective VRPTW Model for Non-adjacent Products

Received: 30 October 2016     Accepted: 26 December 2016     Published: 12 January 2017
Views:       Downloads:
Abstract

Vehicle Routing Problem (VRP) with time windows is a generalization of the classic VRP. Specifically, every customer must be met in a certain time window. Sometimes in the real life, it is not possible to carry different products simultaneously. In other words, these products are non-adjacent. This paper presents a comprehensive model for the vehicle routing problem with time windows and the possibility of delivery split of non-adjacent products. The proposed model is an extension of VRP considering the profit in a bi-objective optimization model.

Published in American Journal of Science, Engineering and Technology (Volume 2, Issue 1)
DOI 10.11648/j.ajset.20170201.11
Page(s) 1-5
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

VRP, Time Window, Bi-objective, Non-adjacent Products

References
[1] Dantzig, G. and Ramser, J. H. ‘The truck dispatching problem’, Management Science, Vol. 6, pp. 80-91.
[2] Lenstra, J. and Rinnooy, K. ‘Complexity of vehicle routing and scheduling problems’, Networks, Vol.
[3] Baños, R., Ortega, J., Gil, C., Fernández, A. and de Toro, F. (2013) ‘A Simulated Annealing-based parallel multi-objective approach to vehicle routing problems with time windows’, Expert Systems with Applications, Vol. 40, Issue 5, pp. 1696–1707.
[4] Wang, C., Mu, D., Zhao, F. and Sutherland, J. W. (2015) ‘A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup–delivery and time windows’. Computers & Industrial Engineering, Vol. 83, pp. 111–122.
[5] Ursani, Z., Essam, D., Cornforth, D. and Stocker, R. (2011) ‘Localized genetic algorithm for vehicle routing problem with time windows’, Applied Soft Computing, Vol. 11, Issue 8, pp. 5375–5390.
[6] Yang, B., Hu, Z.-H., Wei, C., Li, S.-Q., Zhao, L. and Jia, S. (2015) ‘Routing with time-windows for multiple environmental vehicle types’, Computers & Industrial Engineering, Vol. 89, pp. 150-161.
[7] Belhaiza, S., Hansen, P. and Laporte, G. (2014) ‘A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows’. Computers & Operations Research, Vol. 52, pp. 269–281.
[8] Li, X., Tian, P. and Leung, C. H. (2010) ‘Vehicle routing problems with time windows and stochastic travel and service times: Models and algorithm’, International Journal of Production Economics, Vol. 125, pp. 137–145.
[9] Zare-Reisabadi, E. and Mirmohammadi, S. H. (2015) ‘Site dependent vehicle routing problem with soft time window: Modeling and solution approach’. Computers & Industrial Engineering, Vol. 90, pp. 177-185.
[10] Yu, B., Yang, Z. Z. and Yao, B. Z. (2011) ‘A hybrid algorithm for vehicle routing problem with time windows’, Expert Systems with Applications, Vol. 38, pp. 435–441.
[11] Küçükoglu, I., and Öztürk, N. (2015) ‘An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows’, Computers & Industrial Engineering, Vol. 86, pp. 60-68.
[12] Belfiore, P. and Yoshizaki, H. T. Y. (2013) ‘Heuristic methods for the fleet size and mix vehicle routing problem with time windows and split deliveries’, Computers & Industrial Engineering, Vol. 64, pp. 589–601.
[13] Cherkesly, M., Desaulniers, G. and Laporte, G. (2015) ‘A population-based metaheuristic for the pickup and delivery problem with time windows and LIFO loading’, Computers & Operations Research, Vol. 62, pp. 23-35.
[14] Dror, M. and Trudeau, P. (1989) ‘Savings by split delivery routing’, Transportation Science, Vol. 23, pp. 141–145.
[15] Dror, M., Laporte, G. and Trudeau, P. (1994) ‘Vehicle routing with split deliveries’, Discrete Applied Mathematics, Vol. 50 (3), pp. 239–354.
[16] El-Sherbeny, N. (2010) ‘Vehicle routing with time windows: An overview of exact, heuristic and metaheuristic methods’, Journal of King Saud University (Science), Vol. 22, pp. 123–131.
[17] Dell’Amico, M., Maffioli, F. and Varbrand, P. (1995) ‘On prize-collecting tours and the asymmetric travelling salesman problem’, International Transactions in Operational Research, Vol. 2, pp. 297–308.
[18] Keller, C. P. and Goodchild, M. (1988) ‘the multi objective vending problem: A generalization of the traveling salesman problem’, Environment and Planning B: Planning and Design, Vol. 15, pp. 447-460.
[19] Feillet, D., Dejax, P. and Gendreau, M. (2005) ‘Traveling salesman problems with profits’, Transportation Science, Vol. 36, pp. 188–205.
[20] Laporte, G. and Martello, S. (1990) ‘The selective traveling salesman problem’, Discrete Applied Mathematics, Vol. 26, pp. 193–207.
[21] Ausiello, G., Bonifaci, V. and Laura, L. (2008) ‘The online Prize-Collecting Traveling Salesman Problem’, Information Processing Letters, Vol. 107, pp. 199–204.
[22] Pedro, O., Saldanha, R. and Camargo, R. (2013) ‘A Tabu Search Approach for the Prize Collecting Traveling Salesman Problem’, Electronic Notes in Discrete Mathematics, Vol. 41, pp. 261–268.
[23] Archetti, C., Feillet, D., Hertz, A. and Speranza, M. G. (2010) ‘The undirected capacitated arc routing problem with profits’, Computers & Operations Research, Vol. 37, pp. 1860–1869.
[24] Chao, I., Golden, B. and Wasil, E. (1996) ‘The team orienteering problem’, European Journal of Operational Research, Vol. 88, pp. 464–474.
[25] Lin, S.-W. and Yu., V. F. (2015) ‘A simulated annealing heuristic for the multiconstraint team orienteering problem with multiple time windows’, Applied Soft Computing, Vol. 37, p.p. 632-642.
[26] Boussier, S., Feillet, D. and Gendreau, M. (2007) ‘An exact algorithm for team orienteering problems’, 4OR, Vol. 5, pp. 211–230.
[27] Aráoz, J., Fernández, E. and Meza, O. (2009) ‘Solving the prize-collecting rural postman problem’, European Journal of Operational Research, Vol. 196, pp. 886–896.
[28] Mavrotas, G. (2009) ‘Effective implementation of the e-constraint method in Multi Objective Mathematical Programming problems’, Applied Mathematics and Computation, Vol. 213, pp. 455–465.
[29] Mavrotas, G. and Florios, K. (2013) ‘An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems’, Applied Mathematics and Computation, Vol. 219, pp. 9652–9669.
Cite This Article
  • APA Style

    Mohammad Hossein Sarbaghi Yazdi, Farhad Esmaeili. (2017). A Bi-objective VRPTW Model for Non-adjacent Products. American Journal of Science, Engineering and Technology, 2(1), 1-5. https://doi.org/10.11648/j.ajset.20170201.11

    Copy | Download

    ACS Style

    Mohammad Hossein Sarbaghi Yazdi; Farhad Esmaeili. A Bi-objective VRPTW Model for Non-adjacent Products. Am. J. Sci. Eng. Technol. 2017, 2(1), 1-5. doi: 10.11648/j.ajset.20170201.11

    Copy | Download

    AMA Style

    Mohammad Hossein Sarbaghi Yazdi, Farhad Esmaeili. A Bi-objective VRPTW Model for Non-adjacent Products. Am J Sci Eng Technol. 2017;2(1):1-5. doi: 10.11648/j.ajset.20170201.11

    Copy | Download

  • @article{10.11648/j.ajset.20170201.11,
      author = {Mohammad Hossein Sarbaghi Yazdi and Farhad Esmaeili},
      title = {A Bi-objective VRPTW Model for Non-adjacent Products},
      journal = {American Journal of Science, Engineering and Technology},
      volume = {2},
      number = {1},
      pages = {1-5},
      doi = {10.11648/j.ajset.20170201.11},
      url = {https://doi.org/10.11648/j.ajset.20170201.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20170201.11},
      abstract = {Vehicle Routing Problem (VRP) with time windows is a generalization of the classic VRP. Specifically, every customer must be met in a certain time window. Sometimes in the real life, it is not possible to carry different products simultaneously. In other words, these products are non-adjacent. This paper presents a comprehensive model for the vehicle routing problem with time windows and the possibility of delivery split of non-adjacent products. The proposed model is an extension of VRP considering the profit in a bi-objective optimization model.},
     year = {2017}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - A Bi-objective VRPTW Model for Non-adjacent Products
    AU  - Mohammad Hossein Sarbaghi Yazdi
    AU  - Farhad Esmaeili
    Y1  - 2017/01/12
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ajset.20170201.11
    DO  - 10.11648/j.ajset.20170201.11
    T2  - American Journal of Science, Engineering and Technology
    JF  - American Journal of Science, Engineering and Technology
    JO  - American Journal of Science, Engineering and Technology
    SP  - 1
    EP  - 5
    PB  - Science Publishing Group
    SN  - 2578-8353
    UR  - https://doi.org/10.11648/j.ajset.20170201.11
    AB  - Vehicle Routing Problem (VRP) with time windows is a generalization of the classic VRP. Specifically, every customer must be met in a certain time window. Sometimes in the real life, it is not possible to carry different products simultaneously. In other words, these products are non-adjacent. This paper presents a comprehensive model for the vehicle routing problem with time windows and the possibility of delivery split of non-adjacent products. The proposed model is an extension of VRP considering the profit in a bi-objective optimization model.
    VL  - 2
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran

  • Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran

  • Sections