International audienceWe present a general framework for solving a real-world multi-modal home-healthcare scheduling (MHS) problem from a major Austrian home-healthcare provider. The goal of MHS is to assign home-care staff to customers and determine efficient multimodal tours while considering staff and customer satisfaction. Our approach is designed to be as problem-independent as possible, such that the resulting methods can be easily adapted to MHS setups of other home-healthcare providers. We chose a two-stage approach: in the first stage, we generate initial solutions either via constraint programming techniques or by a random procedure. During the second stage, the initial solutions are (iteratively) improved by applying one of four metaheuristics: variable neighborhood search, a memetic algorithm, scatter search and a simulated annealing hyper-heuristic. An extensive computational comparison shows that the approach is capable of solving real-world instances in reasonable time and produces valid solutions within only a few seconds
The last-mile in the courier express parcel (CEP) sector is the most challenging part of the overall transport chain. This is, among other reasons, because many recipients are not at home when deliveries take place. On the other hand, it is for many recipients inconvenient that they have to collect their parcels at different pickup shops varying from logistics service provider (LSP) to LSP. One solution is to employ (open) parcel lockers which are conveniently located for recipients and which allow successful (first) deliveries for LSPs. In this paper, we investigate the impact of parcel lockers with respect to traveled distances as well as CO2 emissions. We show that under certain situations, parcel lockers positively contribute to both aforementioned performance indexes. Based on our observations, we formulate recommendations how to support the implementation of parcel lockers.
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