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Bi-objective Optimization for Joint Production Scheduling and Distribution Problem with Sustainability

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Computational Logistics (ICCL 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13004))

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Abstract

This paper considers joint production and distribution planning problem with environmental factors. While the production phase of the problem consists of job shop production environment running under Just-In-Time (JIT) philosophy, the distribution phase involves a heterogeneous fleet of vehicles with regards to capacity and fuel consumption rate. Therefore, we tackle two well-known problems in Operations Research terminology which are called machine scheduling and vehicle routing problems. The joint problem is formulated as a bi-objective structure, the first of which is to minimize the maximum tardiness, the second of which aims to minimize the total amount of CO2 emitted by the vehicles. Orders are required to be consolidated to reduce the traveling time, distance, or cost. An increase in the vehicle capacity results in a higher possibility of consolidation, but in this case, the amount of CO2 emission that the vehicle emits into the air will also increase. Having shown that two objectives are conflicting in an illustrative example, we formulate the problem as a mixed integer programming (MIP) formulation and use an Augmented Epsilon Constraint Method (AUGMECON) for solving the bi-objective model. On randomly generated test instances, the applicability of the MIP model through the use of AUGMECON is reported.

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References

  1. Chandra, P., Fisher, M.L.: Coordination of production and distribution planning. Eur. J. Oper. Res. 72(3), 503–517 (1994)

    Article  Google Scholar 

  2. Moons, S., Ramaekers, K., Caris, A., Arda, Y.: Integrating production scheduling and vehicle routing decisions at the operational decision level: a review and discussion. Comput. Ind. Eng. 104, 224–245 (2017)

    Article  Google Scholar 

  3. Scholz-Reiter, B., Makuschewitz, T., Novaes, A.G., Frazzon, E.M., Lima, O.F., Jr.: An approach for the sustainable integration of production and transportation scheduling. Int. J. Logist. Syst. Manag. 10(2), 158–179 (2011)

    Google Scholar 

  4. Meinecke, C., Scholz-Reiter, B.: A heuristic for the integrated production and distribution scheduling problem. Int. Sci. Index 8(2), 290–297 (2014)

    Google Scholar 

  5. Ramezanian, R., Mohammadi, S., Cheraghalikhani, A.: Toward an integrated modeling approach for production and delivery operations in flow shop system: trade-off between direct and routing delivery methods. J. Manuf. Syst. 44, 79–92 (2017)

    Article  Google Scholar 

  6. Wang, S., Wu, R., Chu, F., Yu, J.: Variable neighborhood search-based methods for integrated hybrid flow shop scheduling with distribution. Soft. Comput. 24(12), 8917–8936 (2019). https://doi.org/10.1007/s00500-019-04420-6

    Article  Google Scholar 

  7. Mohammadi, S., Al-e-Hashem, S.M., Rekik, Y.: An integrated production scheduling and delivery route planning with multi-purpose machines: a case study from a furniture manufacturing company. Int. J. Prod. Econ. 219, 347–359 (2019)

    Google Scholar 

  8. Yağmur, E., Kesen, S.E.: A memetic algorithm for joint production and distribution scheduling with due dates. Comput. Ind. Eng. 142, 106342 (2020)

    Google Scholar 

  9. Farahani, P., Grunow, M., Günther, H.-O.: Integrated production and distribution planning for perishable food products. Flex. Serv. Manuf. J. 24(1), 28–51 (2012)

    Article  Google Scholar 

  10. Jamili, N., Ranjbar, M., Salari, M.: A bi-objective model for integrated scheduling of production and distribution in a supply chain with order release date restrictions. J. Manuf. Syst. 40, 105–118 (2016)

    Article  Google Scholar 

  11. Ganji, M., Kazemipoor, H., Molana, S.M.H., Sajadi, S.M.: A green multi-objective integrated scheduling of production and distribution with heterogeneous fleet vehicle routing and time windows. J. Clean. Prod. 259, 120824 (2020)

    Google Scholar 

  12. Xiao, Y., Zhao, Q., Kaku, I., Xu, Y.: Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Comput. Oper. Res. 39(7), 1419–1431 (2012)

    Article  MathSciNet  Google Scholar 

  13. Zhang, S., Lee, C., Choy, K., Ho, W., Ip, W.: Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem. Transp. Res. Part D: Transp. Environ. 31, 85–99 (2014)

    Article  Google Scholar 

  14. Bektaş, T., Laporte, G.: The pollution-routing problem. Transp. Res. Part B: Methodol. 45(8), 1232–1250 (2011)

    Article  Google Scholar 

  15. Kirschstein, T., Meisel, F.: GHG-emission models for assessing the eco-friendliness of road and rail freight transports. Transp. Res. Part B: Methodol. 73, 13–33 (2015)

    Article  Google Scholar 

  16. Franceschetti, A., Demir, E., Honhon, D., Van Woensel, T., Laporte, G., Stobbe, M.: A metaheuristic for the time-dependent pollution-routing problem. Eur. J. Oper. Res. 259(3), 972–991 (2017)

    Article  MathSciNet  Google Scholar 

  17. Talaei, M., Moghaddam, B.F., Pishvaee, M.S., Bozorgi-Amiri, A., Gholamnejad, S.: A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry. J. Clean. Prod. 113, 662–673 (2016)

    Article  Google Scholar 

  18. Toro, E.M., Franco, J.F., Echeverri, M.G., Guimarães, F.G.: A multi-objective model for the green capacitated location-routing problem considering environmental impact. Comput. Ind. Eng. 110, 114–125 (2017)

    Article  Google Scholar 

  19. Mavrotas, G.: Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Appl. Math. Comput. 213(2), 455–465 (2009)

    MathSciNet  MATH  Google Scholar 

  20. Haimes, Y.: On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE Trans. Syst. Man Cybern. 1(3), 296–297 (1971)

    MathSciNet  MATH  Google Scholar 

  21. Mavrotas, G.: Generation of efficient solutions in multiobjective mathematical programming problems using GAMS. Effective implementation of the ε-constraint method. Lecturer, Laboratory of Industrial and Energy Economics, School of Chemical Engineering. National Technical University of Athens (2007)

    Google Scholar 

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Authors and Affiliations

  1. Konya Technical University, Selcuklu, Konya, Turkey

    Ece Yağmur & Saadettin Erhan Kesen

Authors
  1. Ece Yağmur
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  2. Saadettin Erhan Kesen
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Correspondence to Saadettin Erhan Kesen .

Editor information

Editors and Affiliations

  1. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Martijn Mes

  2. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Eduardo Lalla-Ruiz

  3. IWI-Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Stefan Voß

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Yağmur, E., Kesen, S.E. (2021). Bi-objective Optimization for Joint Production Scheduling and Distribution Problem with Sustainability. In: Mes, M., Lalla-Ruiz, E., Voß, S. (eds) Computational Logistics. ICCL 2021. Lecture Notes in Computer Science(), vol 13004. Springer, Cham. https://doi.org/10.1007/978-3-030-87672-2_18

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  • DOI: https://doi.org/10.1007/978-3-030-87672-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87671-5

  • Online ISBN: 978-3-030-87672-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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