Solving Vehicle Routing Problem with Time Windows with Hybrid Evolutionary Algorithm

2010 ◽  
Author(s):  
Yong Mao ◽  
Yanfang Deng
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Routing Problem ◽  
Hybrid Evolutionary Algorithm

scholarly journals Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm

2020 ◽  
Vol 12 (5) ◽  
pp. 2127
Author(s):  
Bo Peng ◽  
Lifan Wu ◽  
Yuxin Yi ◽  
Xiding Chen
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Carbon Dioxide Emission ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Hybrid Evolutionary Algorithm ◽  
Multiple Depots ◽  
Human Pollution ◽  
Distinct Features

The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.

Sign in / Sign up

Export Citation Format

Share Document