Variable Neighborhood Search for the Time-Dependent Vehicle Routing Problem with Soft Time Windows

2011 ◽  
pp. 61-75 ◽  
Author(s):  
Stefanie Kritzinger ◽  
Fabien Tricoire ◽  
Karl F. Doerner ◽  
Richard F. Hartl
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Time Windows ◽  
Time Dependent ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Soft Time Windows

scholarly journals Pengembangan Algoritma Hybrid Restart Simulated Annealing with Variable Neighborhood Search (HRSA-VNS) untuk penyelesaian kasus Vehicle Routing Problem with Time Windows (VRPTW)

2017 ◽  
Vol 6 (1) ◽  
pp. 49
Author(s):  
Titi Iswari
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Simulated Annealing Algorithm ◽  
Time Windows ◽  
Heuristic Method ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Time Required

<p><em>Determining the vehicle routing is one of the important components in existing logistics systems. It is because the vehicle route problem has some effect on transportation costs and time required in the logistics system. In determining the vehicle routes, there are some restrictions faced, such as the maximum capacity of the vehicle and a time limit in which depot or customer has a limited or spesific opening hours (time windows). This problem referred to Vehicle Routing Problem with Time Windows (VRPTW). To solve the VRPTW, this study developed a meta-heuristic method called Hybrid Restart Simulated Annealing with Variable Neighborhood Search (HRSA-VNS). HRSA-VNS algorithm is a modification of Simulated Annealing algorithm by adding a restart strategy and using the VNS algorithm scheme in the stage of finding neighborhood solutions (neighborhood search phase). Testing the performance of HRSA-VNS algorithm is done by comparing the results of the algorithm to the Best Known Solution (BKS) and the usual SA algorithm without modification. From the results obtained, it is known that the algorithm perform well enough in resolving the VRPTW case with the average differences are -2.0% with BKS from Solomon website, 1.83% with BKS from Alvarenga, and -2.2% with usual SA algorithm without any modifications.</em></p><p><em>Keywords : vehicle routing problem, time windows, simulated annealing, VNS, restart</em></p>

scholarly journals A Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

2004 ◽  
Vol 10 (6) ◽  
pp. 613-627 ◽  
Author(s):  
Michael Polacek ◽  
Richard F. Hartl ◽  
Karl Doerner ◽  
Marc Reimann
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Time Windows ◽  
Neighborhood Search ◽  
Routing Problem
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