A Multi-Trip Split-Delivery Vehicle Routing Problem with Time Windows for Inventory Replenishment Under Stochastic Travel Times

2015 ◽  
Vol 17 (1) ◽  
pp. 41-68 ◽  
Author(s):  
James C. Chu ◽  
Shangyao Yan ◽  
Han-Jheng Huang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Travel Times ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Split Delivery ◽  
Inventory Replenishment ◽  
Stochastic Travel Times

scholarly journals The Split Delivery Vehicle Routing Problem with Time Windows and Customer Inconvenience Constraints

2019 ◽  
Vol 53 (4) ◽  
pp. 1067-1084 ◽  
Author(s):  
Nicola Bianchessi ◽  
Michael Drexl ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Split Delivery

scholarly journals A Three-Stage Saving-Based Heuristic for Vehicle Routing Problem with Time Windows and Stochastic Travel Times

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Zheng Wang ◽  
Chunyue Zhou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Travel Times ◽  
Start Time ◽  
Routing Problem ◽  
Problem Transformation ◽  
Basic Ideas ◽  
Two Stages ◽  
Stochastic Travel Times

This paper presents a saving-based heuristic for the vehicle routing problem with time windows and stochastic travel times (VRPTWSTT). One of the basic ideas of the heuristic is to advance the latest service start time of each customer by a certain period of time. In this way, the reserved time can be used to cope with unexpected travel time delay when necessary. Another important idea is to transform the VRPTWSTT to a set of vehicle routing problems with time windows (VRPTW), each of which is defined by a given percentage used to calculate the reserved time for customers. Based on the above two key ideas, a three-stage heuristic that includes the “problem transformation” stage, the “solution construction” stage, and the “solution improvement” stage is developed. After the problem transformation in the first stage, the work of the next two stages is to first construct an initial solution for each transformed VRPTW by improving the idea of the classical Clarke-Wright heuristic and then further improve the solution. Finally, a number of numerical experiments are conducted to evaluate the efficiency of the described methodology under different uncertainty levels.

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