Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1267-1284 ◽  
Author(s):  
Yandong He ◽  
Xu Wang ◽  
Fuli Zhou ◽  
Yun Lin

Purpose This paper aims to study the vehicle routing problem with dynamic customers considering dual service (including home delivery [HD] and customer pickup [CP]) in the last mile delivery in which three decisions have to be made: determine routes that lie along the HD points and CP facilities; optimize routes in real time, which mode is better between simultaneous dual service (SDS, HD points and CP facilities are served simultaneously by the same vehicle); and respective dual service (RDS, HD points and CP facilities are served by different vehicles)? Design/methodology/approach This paper establishes a mixed integer linear programing model for the dynamic vehicle routing problem considering simultaneous dual services (DVRP-SDS). To increase the practical usefulness and solve large instances, the authors designed a two-phase matheuristic including construction-improvement heuristics to solve the deterministic model and dynamic programing to adjust routes to dynamic customers. Findings The computational experiments show that the CP facilities offer greater flexibility for adjusting routes to dynamic customers and that the SDS delivery system outperforms the RDS delivery system in terms of cost and number of vehicles used. Practical implications The results provide managerial insights for express enterprises from the perspective of operation research to make decisions. Originality/value This paper is among the first papers to study the DVRP-SDS. Moreover, this paper guides the managers to select better delivery mode in the last mile delivery.

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shifeng Chen ◽  
Rong Chen ◽  
Jian Gao

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.


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