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A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery

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  • Karaoglan, Ismail
  • Altiparmak, Fulya
  • Kara, Imdat
  • Dengiz, Berna

Abstract

This paper addresses a location-routing problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. We propose an effective branch-and-cut algorithm for solving the LRPSPD. The proposed algorithm implements several valid inequalities adapted from the literature for the problem and a local search based on simulated annealing algorithm to obtain upper bounds. Computational results, for a large number of instances derived from the literature, show that some instances with up to 88 customers and 8 potential depots can be solved in a reasonable computation time.

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  • Karaoglan, Ismail & Altiparmak, Fulya & Kara, Imdat & Dengiz, Berna, 2011. "A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery," European Journal of Operational Research, Elsevier, vol. 211(2), pages 318-332, June.
    • Handle: RePEc:eee:ejores:v:211:y:2011:i:2:p:318-332
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    7. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
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    13. Capelle, Thomas & Cortés, Cristián E. & Gendreau, Michel & Rey, Pablo A. & Rousseau, Louis-Martin, 2019. "A column generation approach for location-routing problems with pickup and delivery," European Journal of Operational Research, Elsevier, vol. 272(1), pages 121-131.
    14. Xiong Qiang & Martinson Yeboah Appiah & Kwasi Boateng & Frederick VonWolff Appiah, 2020. "Route optimization cold chain logistic distribution using greedy search method," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1115-1130, December.
    15. Yanwei Zhao & Longlong Leng & Chunmiao Zhang, 2021. "A novel framework of hyper-heuristic approach and its application in location-routing problem with simultaneous pickup and delivery," Operational Research, Springer, vol. 21(2), pages 1299-1332, June.
    16. Vincent F. Yu & Shin-Yu Lin, 2016. "Solving the location-routing problem with simultaneous pickup and delivery by simulated annealing," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 526-549, January.
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    18. Karaoğlan, İsmail & Erdoğan, Güneş & Koç, Çağrı, 2018. "The Multi-Vehicle Probabilistic Covering Tour Problem," European Journal of Operational Research, Elsevier, vol. 271(1), pages 278-287.
    19. Jing Chen & Pengfei Gui & Tao Ding & Sanggyun Na & Yingtang Zhou, 2019. "Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
    20. Hunkar Toyoglu & Oya Karasan & Bahar Kara, 2012. "A New Formulation Approach for Location-Routing Problems," Networks and Spatial Economics, Springer, vol. 12(4), pages 635-659, December.
    21. Çağrı Koç, 2019. "Analysis of vehicle emissions in location-routing problem," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 1-33, March.
    22. Zare Mehrjerdi, Yahia & Nadizadeh, Ali, 2013. "Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands," European Journal of Operational Research, Elsevier, vol. 229(1), pages 75-84.
    23. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.

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