last mile transport

This paper presents a methodology for assessing bicycle first-last mile trips from one area to many possible areas using three visualizations on accessibility, travel times, and transit mode(s) utilized.

As e-retailers compete with increasingly consumer-focused service, urban freight witnesses a significant increase in associated distribution costs and negative externalities including greenhouse gas emissions advancing global climate change, as well as criteria pollutant emissions worsening local air quality and thus affecting those living close to logistics clusters. Thus, the author considers the potential of e-commerce to render economically viable, environmentally efficient, and socially equitable urban goods flow, which is pertinent to understand the opportunities and challenges associated with urban freight in light of the increasingly consumer-focused e-commerce distribution.

This study investigates the opportunities and challenges associated with alternate last-mile distribution strategies for an e-retailer offering expedited service with rush delivery within strict timeframes. The authors formulated a last-mile network design (LMND) problem as a dynamic-stochastic two-echelon capacitated location routing problem with time-windows (DS-2E-C-LRP-TW) addressed with an adaptive large neighborhood search (ALNS) metaheuristic.

This work models a last-mile network design problem for an e-retailer with a capacitated two-echelon distribution structure - typical in e-retail last-mile distribution, catering to a market with a stochastic and dynamic daily customer demand requesting delivery within time-windows.

This is the dataset associated with the report "Simulating Bike-Transit Trips Using BikewaySim and TransitSim."