A decision model for last-mile delivery planning with crowdsourcing integration

Kuan-cheng Huang*, Muhammad Nashir Ardiansyah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Crowdsourced transportation has been playing a more important role when faced with the growing demand for last-mile delivery, mainly due to the booming e-commerce. Crowdsourced delivery offers greater flexibility and requires less capital investment than traditional outsourcing approaches. This study deals with the planning of the last-mile delivery with partial crowdsourcing integration, in which crowdsourcing helps to manage the delivery from a transfer point to final customer locations. The decision involves several basic questions, including which customer is to be outsourced, by which outsourcing partner, and at which transfer point. The decision problem is formulated as a mixed integer programing (MIP) model. In addition, a heuristics algorithm has been designed to handle large-scale problems. Based on the numerical experiment, the heuristics algorithm can generate a good quality solution within an acceptable computation time. In general, this study shows that well-planned crowdsourcing integration can take advantage of the flexibility and cost saving of crowdsourcing for last-mile delivery.

Original languageEnglish
Pages (from-to)898-912
Number of pages15
JournalComputers and Industrial Engineering
StatePublished - 1 Sep 2019


  • Crowdsourced delivery
  • Last-mile delivery
  • Mixed integer programming
  • Tabu search heuristics
  • Two echelon routing problem


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