A Variable Neighborhood Tabu Search Algorithm for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows
Wei Luo, Fu Zhuo
Abstract
Wei Luo, Fu Zhuo
Abstract
The heterogeneous fleet vehicle routing problem with time windows is a variant of the classical vehicle routing problem. This paper defines a mathematical model of this problem and proposes a variable neighborhood tabu search algorithm to solve it. The initial solution is obtained by GENIUS and the giant tour algorithm. Our algorithm employs a variable neighborhood mechanism to search the optimal solution based upon four neighborhoods. In addition, the local search results are improved by the tabu search algorithm. The proposed algorithm appears to be effective when tested on benchmark instances from the literature.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The heterogeneous fleet vehicle routing problem with time windows is a variant of the classical vehicle routing problem. This paper defines a mathematical model of this problem and proposes a variable neighborhood tabu search algorithm to solve it. The initial solution is obtained by GENIUS and the giant tour algorithm. Our algorithm employs a variable neighborhood mechanism to search the optimal solution based upon four neighborhoods. In addition, the local search results are improved by the tabu search algorithm. The proposed algorithm appears to be effective when tested on benchmark instances from the literature.
Key concepts: Tabu search, Vehicle routing problem, Benchmark (surveying), Guided Local Search, Mathematical optimization, Variable neighborhood search, Variable (mathematics), Computer science