Open AccessA TSP-based nested clustering approach to solve multi-depot heterogeneous fleet routing problem
Author(s) -
Mohammad Hassan Shojaeefard,
Morteza Mollajafari,
S. Mousavitabar,
M. Khordehbinan,
H. Hosseinalibeiki
Publication year - 2022
Publication title -
revista internacional de métodos numéricos para cálculo y diseño en ingeniería
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.213
H-Index - 9
eISSN - 1886-158X
pISSN - 0213-1315
DOI - 10.23967/j.rimni.2022.03.001
Subject(s) - vehicle routing problem , computer science , cluster analysis , travelling salesman problem , mathematical optimization , heuristic , routing (electronic design automation) , column generation , algorithm , mathematics , artificial intelligence , computer network
The distribution of goods and urban services has made the issue of vehicle routing of particular importance to researchers. Advanced Routing Vehicle (RVRP) Rich Vehicle Routing Problem As a hybrid optimization problem, it is widely used in many transportation and logistics planning. The approach of this paper is to present a heuristic method for solving the problem called Nested Clustering for Traveling Salesman Problem (NC-TSP), in this method to optimize the search space, we break the problem in consecutive space. In the first step, using the nearest neighbor (Knn) algorithm with the center of each depot, and then using the fuzzy C-means clustering method within each cluster obtained from the Knn method, to find the optimal set of nodes. Then we solve the problem using the extension of MILP linear functions to the heterogeneous nature of the transport fleet and the warehouses that supply the goods, using the optimization algorithm (GA). The proposed approach, despite its great complexity, solves the problem to a large extent and shows promising cost-effective results in the existing criteria.