Searching for a Safe Shortest Path in a Warehouse

Aurélien Mombelli, Alain Quilliot, Mourad Baiou

2022

Abstract

In this paper, we deal with a fleet of autonomous vehicles which is required to perform internal logistics tasks inside some protected areas. This fleet is supposed to be ruled by a hierarchical supervision architecture which, at the top level, distributes and schedules Pick up and Delivery tasks, and, at the lowest level, ensures safety at the crossroads and controls the trajectories. We focus here on the top level and deals with the problem which consist in inserting an additional vehicle into the current fleet and routing it while introducing a time dependent estimation of the risk induced by the traversal of any arc at a given time. We propose a model and design a bi-level heuristic and an A*-like heuristic which both rely on a reinforcement learning scheme in order to route and schedule this vehicles according to a well-fitted compromise between speed and risk.

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Paper Citation


in Harvard Style

Mombelli A., Quilliot A. and Baiou M. (2022). Searching for a Safe Shortest Path in a Warehouse. In Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-548-7, pages 115-122. DOI: 10.5220/0010780700003117


in Bibtex Style

@conference{icores22,
author={Aurélien Mombelli and Alain Quilliot and Mourad Baiou},
title={Searching for a Safe Shortest Path in a Warehouse},
booktitle={Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2022},
pages={115-122},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010780700003117},
isbn={978-989-758-548-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Searching for a Safe Shortest Path in a Warehouse
SN - 978-989-758-548-7
AU - Mombelli A.
AU - Quilliot A.
AU - Baiou M.
PY - 2022
SP - 115
EP - 122
DO - 10.5220/0010780700003117