Personal Shopper Systems in Last-Mile Logistics - Instant Delivery Problem (IDP) Rolling Horizon Framework

Sep 13, 2026

Uploaded by Rowan

Instant grocery delivery operations are analyzed through two inventory sourcing strategies: Personal Shopper Systems (PSS) and Inventory Owned Delivery (IOD). In PSS, couriers visit affiliated brick-and-mortar stores to purchase and deliver ordered items within tight deadlines; in IOD, couriers fulfill orders from a dark-store distribution center managed by the provider. To capture PSS-specific realities such as real-time store selection and in-store collection, an Instant Delivery Problem (IDP) is introduced. A rolling horizon framework with column generation is developed, and computational studies show PSS is highly competitive, especially for small orders and dense retail areas.

LanguageEnglish

CategoryGeneral

FormatPDF

Pages34

Reading Time12 min

AccessFree to download

Introduction

Instant delivery challenges and problem context

Personal Shopper System (PSS)

Inventory Owned Delivery (IOD)

Instant Delivery Problem (IDP) and solution approach

Computational results and observations

Personal Shopper Systems in Last-Mile Logistics J. P. van der Gaast Department of Management Science, Fudan University, [P.R. China jpgaast@fudan.edu.cn](P.R. China jpgaast@fudan.edu.cn) A. M. Arslan Department of Management Science, Lancaster University, United Kingdom, [a.arslan1@lancaster.ac.uk](a.arslan1@lancaster.ac.uk) This paper explores the logistics operations of instant grocery delivery services. We specifically concentrate on two widely adopted strategies: Personal Shopper Systems (PSS) and Inventory Owned Delivery Systems (IOD) . In the PSS, couriers visit affiliated brick and mortar stores in the delivery area to pick and purchase ordered products and deliver them to customers. Whereas in the IOD, couriers collect products from a single distribution center or so-called a dark-store. In the IOD, the inventory of the DC is also managed by the service provider. Even though PSS strategy is asset-light, and hence attractive for investors due to the utilization of existing retailers in the area, maintaining a good level of instant delivery with the PSS is more complex than the IOD. Therefore, we introduce the Instant Delivery Problem (IDP), which explicitly addresses PSS-specific features such as real-time store selection and in-store product collection and can also be used to analyze the IOD. We propose a tailored rolling horizon framework that utilizes column generation to browse updated delivery plans for arriving customer orders. Computational studies both in real-life inspired settings and in case studies on selected urban areas show the PSS is a highly competitive strategy compared to the IOD, particularly when dealing with small-sized customer orders. We observe that the performance of the PSS is robust when varying the delivery service time frame. The case studies also suggest that the PSS becomes even more competitive in areas where the retail store density is high. Key words: Instant Delivery, Personal Shopper Systems, Last-Mile Logistics, Optimization, Dark Stores 1. Introduction Online shopping has become popular due to increased urbanization, rapid e-commerce adaptation, and changed customer expectations (Savelsbergh and Van Woensel 2016, Grand View Research 2019) . Especially, instant delivery is increasingly becoming widespread since it integrates the convenience of online shopping and the immediacy of buying products from a brick and mortar store. As a result, many online platforms around the world have started to offer instant deliveries with shipment times as short as an hour, making these platforms not only a strong competitor to offline shopping but also to traditional online shopping services. Nevertheless, managing an economical and sustainable instant delivery service is challenging as these services share many of the same issues faced by traditional two- Table 1 Examples of instant delivery platforms varying inventory choices as of 2021 | Platform | Speed | Region | Inventory
Source | Operating
strategy | | --- | --- | --- | --- | --- | | Amazon-PrimeNow | In two-hour | North America | Own at a DC | IOD | | Instacart | In one-hour | North America | Affiliated stores | PSS | | GrabMart | As soon as possible | Southeast Asia | Affiliated stores | PSS | | [Getir.com](Getir.com) | As soon as possible | Europe, North America | Own at a DC | IOD | | Meituan | As soon as possible | China | Affiliated stores | PSS | | Ele.Me | As soon as possible | China | Affiliated stores | PSS | | Gorillas | As soon as possible | Europe | Own at a DC | IOD | | CornerShop | As soon as possible | South America | Affiliated stores | PSS | | OneKiosk | As soon as possible | Africa | Affiliated stores | PSS | day and next-day delivery systems (Stroh et al. 2021) . Those are tight order delivery deadlines, low order volumes, and high levels of order variability. This structure leads to inefficient delivery fleet utilization, and consequently, substantial operational expenses (Arslan 2019) . In

FAQs

What is the main difference between PSS and IOD in instant grocery delivery?

In PSS, couriers buy products from affiliated brick-and-mortar stores in the delivery area. In IOD, orders are fulfilled from a single distribution center or dark-store managed by the service provider.

Why introduce the Instant Delivery Problem (IDP)?

IDP explicitly models PSS-specific features, including real-time store selection and in-store product collection, while also enabling analysis of IOD under the same modeling framework.

What method is proposed to generate delivery plans for incoming orders?

The paper proposes a tailored rolling horizon framework that uses column generation to explore updated delivery plans for arriving customer orders.

Sep 13, 2026

Uploaded by Rowan