Simulation-Optimization Approach for Multi-Period Facility Location Problems with Forecasted and Random Demands in a Last-Mile Logistics Application

The introduction of automated parcel locker (APL) systems is one possible approach to improve urban logistics (UL) activities. Based on the city Dortmund as case study, we propose a simulation-optimization integrating system dynamics simulation model (SDSM) with multi-period capacitated facility location problem (CFLP). We this integrated decision support tool for future APL implementations last-mile distribution scheme. First, built causal-loop and stock-flow diagram show main components interdependencies systems. Then, formulated CFLP determine optimal number APLs each period. Finally, used Monte Carlo estimate costs reliability level random demands. evaluate three e-shopper rate scenarios SDSM, then analyze ten detailed demand configurations based results middle-size scenario our model. After 36 months, increases from 99 165 growing demand, stabilizes in all month 24. A middle-demand configuration, which has total about 750,000€, already locates suitable APLs. If budget lower, offers alternatives decision-makers.