Optimization model of vehicle routing problem with heterogenous time windows

Herman Mawengkang, Muhammad Romi Syahputra, Sutarman Sutarman, Gerhard Wilhelm Weber

Abstract


This study proposes a novel optimization framework for the vehicle routing problem with heterogeneous time windows, a critical aspect in logistics and supply chain operations. Unlike conventional vehicle routing problem (VRP) models that assume uniform service schedules and fleet capacities, our approach acknowledges the diverse time constraints and vehicle specifications often encountered in real-world scenarios. By formulating the problem as a mixed integer linear programming model, we incorporate constraints related to time windows, vehicle load capacities, and travel distances. To tackle the NP-hard complexity, we employ a hybrid strategy combining metaheuristic algorithms with exact methods, thus ensuring both solution quality and computational efficiency. Extensive computational experiments, conducted on benchmark datasets and real-world logistics data, confirm the superiority of our model in terms of solution quality, runtime, and adaptability. These findings underscore the model’s practicality for industries facing dynamic routing requirements and tight service windows. Furthermore, the proposed framework equips decision-makers with a robust tool for optimizing route planning, ultimately enhancing service quality, reducing operational costs, and promoting more reliable delivery outcomes.

Keywords


Heterogeneous time windows; Logistics optimization; Metaheuristic algorithms; Mixed integer linear programming; Vehicle routing problem

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DOI: http://doi.org/10.11591/ijece.v15i4.pp4043-4057

Copyright (c) 2025 Herman Mawengkang, Muhammad Romi Syahputra, Sutarman, Gerhard Wilhelm Weber

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES).