Affiliations: [a] School of Information Technology and Management, University of International Business and Economics, Beijing, China
| [b] Department of Mathematical Sciences, University ofCincinnati, Cincinnati, OH, USA
Correspondence:
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Corresponding author. Yaodong Ni, School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China. E-mail: [email protected].
Abstract: In the increasingly competitive logistics industry, much more emphasis has been put on customer satisfaction by firms to distinguish themselves from their competitors. Motivated by the practices, the consistent vehicle routing problem (ConVRP) incorporates service consistency into the vehicle routing problem to improve customer satisfaction. However, the majority of the existing research considers the ConVRP in a deterministic environment while the uncertainties are not fully studied. Therefore, this paper solves the consistent vehicle routing problem under uncertain environment (UnConVRP) taking into account uncertain customer demands, travel times, and service times. Over a multi-day planning horizon, customers may have multi-day or single-day service requirements. The same driver is assigned to each customer almost at the same time each day when customers require service. The objective is to design the routes for vehicles over the planning horizon under uncertain environment while maintaining service consistency. Two uncertain programming models are established based on different decision criteria and the crisp equivalents are proposed using uncertainty theory. An efficient template-based solution framework is designed to solve the models where the artificial bee colony algorithm is embedded. Initially, the template route is constructed to guarantee the service consistency of frequent customers. Then the final daily routes can be derived from the template route. Finally, numerical experiments are performed to show the effectiveness of the proposed algorithm.
