Decision models for order fulfillment processes of online food delivery platforms: a systematic review
Saad Ashraf, Amit Kumar Bardhan
Abstract
Online Delivery Platforms (ODPs) have revolutionised the delivery of restaurant-prepared food. There is a need for a systematic identification and classification of the problems associated with real-time delivery operations of ODPs, as well as an examination of the proposed models to address these issues. This article is the first to review the operational problems faced by ODPs and suggests a categorisation of all existing operational research models on this topic. The research that made the short-list is organised based on problem category, modelling approach, solution method, and performance metrics. ODP operations are grouped into ‘delivery’ and ‘pre-delivery’ processes. Existing research primarily focuses on delivery processes, including tasks such as assigning, routing, scheduling, and dispatching orders. The review highlights the extensive application of optimisation and machine learning in modelling, with a noticeable upward trajectory in the usage of machine learning models. Solution methods have evolved from implementing established algorithms and heuristics to designing novel, problem-specific solutions. Consequently, the scope of performance metrics used to measure solution quality and optimality has also expanded. By consolidating all relevant research, the ensuing discussion enhances the current understanding of the ODP framework. This review also takes the foundational step towards minimising variability in terminology.