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2818. On the Attended Home Delivery Problem with Recovery Options: Economical analysis and solution approaches

Invited abstract in session MC-35: Urban Logistics and sustainable TRAnsportation: OPtimization under uncertainTY and MAchine Learning, stream Stochastic, Robust and Distributionally Robust Optimization.

Monday, 12:30-14:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Daniele Manerba
Dept. of Information Engineering, Università degli Studi di Brescia
2. Valentina Bonomi
CEGIST, Instituto Tècnico Lisboa
3. Renata Mansini
Department of Information Engineering, University of Brescia
4. Roberto Zanotti
Department of Clinical and Experimental Sciences, University of Brescia

Abstract

We study an Attended Home Delivery Problem with Recovery Options (AHDP-RO) as a supporting tool for companies that want to ensure timely services within the complex attended home delivery setting. Since missed deliveries can negatively impact customer satisfaction and delivery costs, the problem considers customers' availability through different profiles identifying the probability of them being at home for each time slot of the delivery day. When a missed delivery occurs, the problem implements different recovery policies based on the customer's preferences (e.g., leaving the package in a safe spot, scheduling a second delivery attempt on the same day, or directing the package to a designated collection point). To optimize the scheduling of deliveries and minimize routing costs, we present a Mixed-Integer Linear Programming formulation in which the cost of a missed delivery is proportional to a penalty (determined by the chosen recovery option) and to the probability of not finding the customer at home during the selected time slot. Moreover, different solution approaches (based on various exact or heuristic technologies) are proposed to solve real-size instances and, in turn, support a multi-attribute analysis for obtaining useful economic and managerial insights on the decisional process we are facing.

Keywords

Status: accepted

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