EURO 2024 Copenhagen
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2599. Enhancing Last-Mile Delivery Efficiency: A Hybrid Simulation-Optimization Approach for Automated Parcel Locker Network

Invited abstract in session MB-29: Combinatorial Optimization models and applications in Logistics and Transportation II, stream Combinatorial Optimization.

Monday, 10:30-12:00
Room: 157 (building: 208)

Authors (first author is the speaker)

1. Javier Faulin
Institute Smart Cities- Dept Statistics and Operations Research, Public University of Navarre
2. Irene Izco
Statitics, Computer Science, and Mathematics, Public University of Navarre
3. Adrian Serrano
Statistics and Operations Research, Public University of Navarre
4. Luis Cadarso
European Institute for Aviation Training and Accreditation, Rey Juan Carlos University
5. Bartosz Sawik
Department of Business Informatics and Engineering Management, AGH University of Science and Technology

Abstract

The disruptions caused by the COVID-19 pandemic have revealed the necessity for innovative last-mile delivery solutions in urban logistics. Thus, automated parcel lockers offer benefits for courier companies and customers by enhancing flexibility and reducing mileage, delivery time, and emissions. This work introduces a novel approach by integrating a System Dynamics Simulation Model to forecast e-commerce demand in Pamplona, Spain, and assesses its scalability for other cities. Additionally, a bi-objective Facility Location Problem (FLP) is rooted within the simulation environment to test various scenarios of demand coverage. Simulation and demand forecasting are conducted using Anylogic software with the CPLEX optimization solver for the FLP, featuring an ε-constraint approach based on economic and demand criteria. Results draw optimal APL networks, derived from the non-dominated solution set of the bi-criteria mathematical programming model through ε parameterization. That leads to the identification of the Pareto Frontier and the trade-offs between the number of lockers and parcel demand satisfied. Finally, we encourage the utility of simulation-optimization in addressing dynamic environments.

Keywords

Status: accepted

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