Efficient hierarchical hybrid delivery in the last mile logistics

Abstract

An efficient hierarchical hybrid delivery (EHHD) model is proposed by integrating a location-allocation optimisation model with a dynamic data envelopment analysis (DEA) model in this paper. The proposed model is characterised by having a periodic measurement assessing customer behaviour using the dynamic DEA, as well as developing a hierarchical connection among home delivery, the pickup point and the locker station options. The developed model considers uncertain conditions for transportation costs and customer behaviour. To solve this model, a meta-goal programming approach has been used. Based on the results of the numerical experiments, the developed model has a better performance than other competing models in terms of generating feasible and optimal solutions. Moreover, the application of the developed model is demonstrated in a case study. To the best of our knowledge, the model presented in this paper is the first attempt to simultaneously integrate customer behaviour with last-mile logistics. [Received: 23 April 2021; Accepted: 27 August 2022]