The Pickup Problem: Consumers' Locational Preferences in Flow Interception

Abstract

This article addresses the pickup problem, wherein patrons briefly interrupt their predetermined journeys to obtain a simple good, such as fast food or a video, and then resume their journeys. This is a problem from the class known as the flow‐interception location problems. Traditional flow‐interception location models (FILMs) are used to select service locations such that the intercepted flows are maximized. In these traditional models, only flow quantities are considered; these models do not consider where a pickup is made in a journey. However, in the real world, consumers often wish to obtain a product or service at or near a specific location along their trips. The pickup model (PUP) proposed here considers consumers' locational preferences, providing a much broader, more realistic approach than FILM (a special case of PUP) to problems in the private and public sectors. By considering which patrons are served where, PUP transforms the FILM into a flow‐interception location‐allocation model, providing a fruitful garden for further research. Geographic information systems and optimization engines are integrated to investigate the PUP model in real‐world transportation systems. Reported findings demonstrate that the optimal locations identified by traditional models arise solely from network flow structure, whereas the optimal locations identified by PUP result from trade‐offs between network flow structure and the importance of proximity to preferred locations. One important discovery is that PUP solutions are superior to those of traditional FILMs if consumers have locational preferences. Up‐to‐date, real‐world transportation networks provide a realistic test‐bed for this and other models of the flow‐interception type.