Abstract
A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory solution from the perspective of platform owner, customers, professional drivers, occasional drivers, and authority, a multi-layer comprehensive model is proposed. To effectively solve the proposed model, we introduce an improved variable neighborhood search (VNS) with a memory-based restart mechanism. The new algorithm is evaluated on instances derived from Solomon’s benchmark and real-life beer delivery instances. Taguchi experiment is used to tune parameters in the proposed VNS, followed by component analysis and real-life experiments. Experimental results indicate that the proposed strategies are effective and the new delivery model in this paper has some advantages over traditional and single-delivery ones from the comprehensive perspectives of stakeholders in the crowdsourcing logistics system.
Highlights
Urbanization and e-commerce are the keys to drive the strong demand for last-mile delivery and same-day delivery services
Inspired by the improvement approach based on memory and learning mechanism, we propose two kinds of methods to record specific attributes which were ever found in elite solution, namely, route-based method and edge-based method
We have proposed a novel vehicle routing problem (VRP) model under the situation of sharing economy from a comprehensive perspective
Summary
Urbanization and e-commerce are the keys to drive the strong demand for last-mile delivery and same-day delivery services. Crowdsourcing logistics (CL) mode is produced in the context of the sharing economy, where the crowd can share their excess transport capacity and spare time [4]. We follow the broader definition by Rai et al [5] who described the CL as “information connectivity enabled marketplace concept that matches supply and demand for logistics services with an undefined and external crowd that has the free capacity with regards to time and/or space, participates voluntarily and is compensated ”. From an environmental perspective, crowdsourcing delivery may help alleviate the traffic congestion problem and reduce carbon emissions. The positive environmental impact of crowd logistics is up for debate in crowdsourcing delivery. Related works and contributions gives the literature review of vehicle routing problem with occasional (crowd) drivers and contributions of this paper.
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