Fuzzy Information Based Vehicle Routing Problem with Improved Hybrid Intelligent Algorithm

Junjie Shen

2022

Abstract

Vehicle routing problem is one of the most popular supply chain management problems, which are at the heart of most decision support systems for real-life distribution problems. The traditional vehicle routing problem (VRP) is often constrained to some specific terms. But in actual situations, the procedure of the travel is full of uncertain elements (i.e. traffic jams et al.). In this paper, an improved hybrid intelligent genetic algorithm is designed to solve fuzzy information constrained VRP. The roulette heuristic algorithm is adopted to create the initial chromosomes with great efficiency. A numerical experiment is presented at the end of this paper to show the efficiency and effectiveness of the hybrid intelligent genetic algorithm under the given condition. Some critical parameters of this algorithm are discussed and some suggestions are proposed in the paper to guide the use of this model in practice.

Paper Citation

in Harvard Style

Shen J. (2022). Fuzzy Information Based Vehicle Routing Problem with Improved Hybrid Intelligent Algorithm. In Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC; ISBN 978-989-758-622-4, SciTePress, pages 5-11. DOI: 10.5220/0011820300003612

in Bibtex Style

@conference{isaic22,
author={Junjie Shen},
title={Fuzzy Information Based Vehicle Routing Problem with Improved Hybrid Intelligent Algorithm},
booktitle={Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC},
year={2022},
pages={5-11},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011820300003612},
isbn={978-989-758-622-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC
TI - Fuzzy Information Based Vehicle Routing Problem with Improved Hybrid Intelligent Algorithm
SN - 978-989-758-622-4
AU - Shen J.
PY - 2022
SP - 5
EP - 11
DO - 10.5220/0011820300003612
PB - SciTePress