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The Latency Location-Routing Problem

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  • Moshref-Javadi, Mohammad
  • Lee, Seokcheon

Abstract

This paper introduces the Latency Location-Routing Problem (LLRP) whose goal is to minimize waiting time of recipients by optimally determining both the locations of depots and the routes of vehicles. The LLRP is customer oriented by pursuing minimization of the latency instead of minimization of the length of routes. One of the main applications of this problem is the distribution of supplies to affected areas in post-disaster relief activities. It is also relevant in customer-oriented supply chain where latency at demand locations plays a significant role in the satisfaction of the customers. The problem is formulated mathematically and two heuristics, the Memetic Algorithm (MA) and the Recursive Granular Algorithm (RGA), are proposed. An extensive experimental study shows that both algorithms are able to produce promising results in reasonable time.

Suggested Citation

  • Moshref-Javadi, Mohammad & Lee, Seokcheon, 2016. "The Latency Location-Routing Problem," European Journal of Operational Research, Elsevier, vol. 255(2), pages 604-619.
    • Handle: RePEc:eee:ejores:v:255:y:2016:i:2:p:604-619
    DOI: 10.1016/j.ejor.2016.05.048
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    2. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
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    4. Xianhua Wu & Yaru Cao & Yang Xiao & Ji Guo, 2020. "Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics," Annals of Operations Research, Springer, vol. 290(1), pages 865-896, July.
    5. Moshref-Javadi, Mohammad & Lee, Seokcheon & Winkenbach, Matthias, 2020. "Design and evaluation of a multi-trip delivery model with truck and drones," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    6. Mohammad Moshref-Javadi & Kristof P. Cauwenberghe & Brent A. McCunney & Ahmad Hemmati, 2023. "Enabling same-day delivery using a drone resupply model with transshipment points," Computational Management Science, Springer, vol. 20(1), pages 1-31, December.
    7. Akbari, Vahid & Shiri, Davood, 2021. "Weighted online minimum latency problem with edge uncertainty," European Journal of Operational Research, Elsevier, vol. 295(1), pages 51-65.
    8. Pouraliakbari-Mamaghani, Mahsa & Saif, Ahmed & Kamal, Noreen, 2023. "Reliable design of a congested disaster relief network: A two-stage stochastic-robust optimization approach," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    9. Maliheh Khorsi & Seyed Kamal Chaharsooghi & Ali Husseinzadeh Kashan & Ali Bozorgi-Amiri, 2022. "Solving the humanitarian multi-trip cumulative capacitated routing problem via a grouping metaheuristic algorithm," Annals of Operations Research, Springer, vol. 319(1), pages 173-210, December.
    10. Bagheri Hosseini, Mozhde & Dehghanian, Farzad & Salari, Majid, 2019. "Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network," European Journal of Operational Research, Elsevier, vol. 272(2), pages 655-673.
    11. Zhuo Sun & Ni Yan & Yining Sun & Haobin Li, 2019. "Location-Routing Optimization with Split Demand for Customer Self-Pickup via Data Analysis and Heuristics Search," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-24, December.
    12. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).

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