Integrated Vehicle Routing and Service Scheduling Under Time and Cancellation Uncertainties with Application in Nonemergency Medical Transportation

Xian Yu (), Siqian Shen () and Huizhu Wang ()
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Xian Yu: Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109
Siqian Shen: Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109
Huizhu Wang: Ford Motor Company, Dearborn, Michigan 48126

Service Science, 2021, vol. 13, issue 3, 172-191

Abstract: In this paper, we consider an integrated vehicle routing and service scheduling problem for serving customers in distributed locations who need pick-up, drop-off, or delivery services. We take into account the random trip time, nonnegligible service time, and possible customer cancellations, under which an ill-designed schedule may lead to undesirable vehicle idleness and customer waiting. We build a stochastic mixed-integer program to minimize the operational cost plus expected penalty cost of customers’ waiting time, vehicles’ idleness, and overtime. Furthermore, to handle real-time arrived service requests, we develop K-means clustering-based algorithms to dynamically update planned routes and schedules. The algorithms assign customers to vehicles based on similarities and then plan schedules on each vehicle separately. We conduct numerical experiments based on diverse instances generated from census data and data from the Ford Motor Company’s GoRide service, to evaluate result sensitivity and to compare the in-sample and out-of-sample performance of different approaches. Managerial insights are provided using numerical results based on different parameter choices and uncertainty settings.

Keywords: pick up and delivery with time windows; appointment scheduling; random cancellation; stochastic integer programming; K-means clustering (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orserv:v:13:y:2021:i:3:p:172-191

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