Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands

2013 ◽  
Vol 4 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Subrata Mitra

Dynamic vehicle routing problems with backhauling (VRPB), although important, have attracted little attention in the literature. Dynamic VRPB is more complex than dynamic vehicle routing problems (VRP) without backhauling, and since VRP without backhauling is a special case of VRPB, models and algorithms for dynamic VRPB can easily be adapted for dynamic VRP. In this paper, the author compared between static and dynamic policies for solving VRPB with dynamic occurrences of customer delivery and pickup demands. They developed heuristic algorithms for medium-sized problems under static and dynamic policies. Although dynamic policies are always at least as good as static policies, the author observed from numerical experimentations that static policies perform relatively well for low degrees of dynamism (dod). On the other hand, dynamic policies are expected to perform significantly better than static policies for high dod and early availabilities of dynamic customer delivery and pickup demand information. The author concludes the paper by providing directions for future research on dynamic VRPB.

2021 ◽  
pp. 107604
Author(s):  
Brenner Humberto Ojeda Rios ◽  
Eduardo C. Xavier ◽  
Flávio K. Miyazawa ◽  
Pedro Amorim ◽  
Eduardo Curcio ◽  
...  

2014 ◽  
pp. 299-347 ◽  
Author(s):  
Tolga Bekta¸s ◽  
Panagiotis P. Repoussis ◽  
Christos D. Tarantilis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Godfrey Chagwiza

A new plant intelligent behaviour optimisation algorithm is developed. The algorithm is motivated by intelligent behaviour of plants and is implemented to solve benchmark vehicle routing problems of all sizes, and results were compared to those in literature. The results show that the new algorithm outperforms most of algorithms it was compared to for very large and large vehicle routing problem instances. This is attributed to the ability of the plant to use previously stored memory to respond to new problems. Future research may focus on improving input parameters so as to achieve better results.


2019 ◽  
Vol 52 (19) ◽  
pp. 359-364
Author(s):  
N.W. Klein Koerkamp ◽  
C. Borst ◽  
Max Mulder ◽  
M.M. van Paassen

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