A decision model for last-mile delivery planning with crowdsourcing integration. (September 2019)

• Record Type: Journal Article
• Authors: Huang, Kuancheng; Ardiansyah, Muhammad Nashir
• Is Part Of: Computers & industrial engineering. Volume 135(2019)
• Page Start: 898
• Page End: 912
• Publication Date: 2019-09
• Subjects: Crowdsourced delivery -- Mixed integer programming -- Last-mile delivery -- Two echelon routing problem -- Tabu search heuristics; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2019.06.059
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Formulating a model for the last-mile delivery with crowdsourcing integration. Developing a solution method with the construction and improvement heuristics. Performing an experiment to affirm the effectiveness of the solution method. Abstract: 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.