Abstract

Last-mile delivery systems are under greater pressure to deliver cost-efficient, reliable, environmentally friendly, and resilient services amid operational challenges. Distance/cost is the usual optimization criterion for traditional vehicle routing methods, and factors related to disruptions, such as the delay frequency, delay severity, and delivery failure risk, are often treated separately or neglected. This study proposes a green-resilient last-mile delivery optimization framework that integrates operational costs, delivery delays, carbon emissions, and operational risk within a single multi-objective decision model. The proposed framework models the capacitated vehicle routing problem with time windows, accounting for vehicle capacity, service time commitments, fuel consumption, emission-level estimates, working hour limits, and lateness penalties and incorporating a disruption-based operational risk score. The risk score is based on the delay frequency, delay severity, and failure probability and can inform routing decisions based on efficiency and resilience. The framework is tested with a case study of urban last-mile delivery and compared with several benchmark scenarios: the current operational plan, a distance-based vehicle routing problem (VRP), a cost-based VRP, a green VRP, and a delay-aware vehicle routing problem with time windows (VRPTW). The results reveal balanced improvements in key performance indicators, in line with the proposed framework. It reduces the total distance by 35.11%, total operational cost by 34.01%, fuel consumption by 10.46%, CO2 emissions by 9.34%, estimated late orders by 93.45%, and total delay minutes by 80.10%, and there are no working hour violations compared to the current case. Other sensitivity, weight, and ablation analyses illustrate the trade-offs among cost/service reliability/environmental goals and risk exposures. The results show that operational risk can be incorporated into the green last-mile routing problem to facilitate more comprehensive—and thus more robust and sustainable—delivery planning in the context of disruptions in urban environments.

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