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Appointment scheduling and routing optimization of attended home delivery system with random customer behavior

Author

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  • Han, Shuihua
  • Zhao, Ling
  • Chen, Kui
  • Luo, Zong-wei
  • Mishra, Deepa

Abstract

Attended home delivery (AHD) has been identified as a crucial delivery mode of the last mile problem. As the name implies, AHD involves delivery of needed goods at the customer's doorsteps or nearby via walking or short-distance vehicle. Considering no-show and random response time, this article presents an integrative approach that combines appointment scheduling and vehicle routing problem with soft time windows. We also propose an intuitive heuristic dynamic programming to tackle the appointment scheduling problem whose optimal decision is expected to be very complicated, embed it into tabu search and formulate a hybrid heuristic algorithmto solve this integrative model. Moreover, an extension to hard time windows has also been discussed. Our results indicate that the integrative approach could lead to high-quality solutions in a reasonable amount of runtimeas compared to the hierarchical approach.

Suggested Citation

  • Han, Shuihua & Zhao, Ling & Chen, Kui & Luo, Zong-wei & Mishra, Deepa, 2017. "Appointment scheduling and routing optimization of attended home delivery system with random customer behavior," European Journal of Operational Research, Elsevier, vol. 262(3), pages 966-980.
    • Handle: RePEc:eee:ejores:v:262:y:2017:i:3:p:966-980
    DOI: 10.1016/j.ejor.2017.03.060
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    Cited by:

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    2. Giuliano, Genevieve & Showalter, Catherine & Yuan, Quan & Zhang, Rui, 2018. "Managing the Impacts of Freight in California," Institute of Transportation Studies, Working Paper Series qt6614p4js, Institute of Transportation Studies, UC Davis.
    3. Dalmeijer, K. & Spliet, R. & Wagelmans, A.P.M., 2019. "Dynamic Time Window Adjustment," Econometric Institute Research Papers EI2019-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Sebastián Dávila & Miguel Alfaro & Guillermo Fuertes & Manuel Vargas & Mauricio Camargo, 2021. "Vehicle Routing Problem with Deadline and Stochastic Service Times: Case of the Ice Cream Industry in Santiago City of Chile," Mathematics, MDPI, vol. 9(21), pages 1-18, October.
    5. Özarık, Sami Serkan & Lurkin, Virginie & Veelenturf, Lucas P. & Van Woensel, Tom & Laporte, Gilbert, 2023. "An Adaptive Large Neighborhood Search heuristic for last-mile deliveries under stochastic customer availability and multiple visits," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 194-220.
    6. Bruno P. Bruck & Filippo Castegini & Jean-François Cordeau & Manuel Iori & Tommaso Poncemi & Dario Vezzali, 2020. "A Decision Support System for Attended Home Services," Interfaces, INFORMS, vol. 50(2), pages 137-152, March.
    7. Zhan, Yang & Wang, Zizhuo & Wan, Guohua, 2021. "Home service routing and appointment scheduling with stochastic service times," European Journal of Operational Research, Elsevier, vol. 288(1), pages 98-110.
    8. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    9. Malichan Thongkham & Sasitorn Kaewman, 2018. "Methodology to Solve the Combination of the Generalized Assignment Problem and the Vehicle Routing Problem: A Case Study in Drug and Medical Instrument Sales and Service," Administrative Sciences, MDPI, vol. 9(1), pages 1-21, December.
    10. Cheng Wang & Runhua Wu & Lili Deng & Yong Chen & Yingde Li & Yuehua Wan, 2020. "A Bibliometric Analysis on No-Show Research: Status, Hotspots, Trends and Outlook," Sustainability, MDPI, vol. 12(10), pages 1-17, May.

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