Open AccessClustering and heuristics algorithm for the vehicle routing problem with time windows
Author(s) -
Andrés Felipe León Villalba,
Elsa Cristina González La Rotta
Publication year - 2022
Publication title -
international journal of industrial engineering computations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.564
H-Index - 26
eISSN - 1923-2926
pISSN - 1923-2934
DOI - 10.5267/j.ijiec.2021.12.002
Subject(s) - vehicle routing problem , heuristics , cluster analysis , computer science , set (abstract data type) , mathematical optimization , algorithm , routing (electronic design automation) , mathematics , artificial intelligence , computer network , programming language
This article presents a novel algorithm based on the cluster first-route second method, which executes a solution through K-means and Optics clustering techniques and Nearest Neighbor and Local Search 2-opt heuristics, for the solution of a vehicle routing problem with time windows (VRPTW). The objective of the problem focuses on reducing distances, supported by the variables of demand, delivery points, capacities, time windows and type of fleet in synergy with the model's taxonomy, based on data referring to deliveries made by a logistics operator in Colombia. As a result, good solutions are generated in minimum time periods after fulfilling the agreed constraints, providing high performance in route generation and solutions for large customer instances. Similarly, the algorithm demonstrates efficiency and competitiveness compared to other methods detailed in the literature, after being benchmarked with the Solomon instance data set, exporting even better results.