{\'E}tude pour l'analyse et l'optimisation du transport des personnes en situation de handicap

TL;DR

This paper addresses optimizing shared medical transportation for people with disabilities in France, aiming to reduce costs while maintaining service quality through advanced routing algorithms.

Contribution

It introduces a novel approach to the Time-Consistent Dial-a-Ride Problem using Large Neighborhood Search and set covering techniques for efficient route optimization.

Findings

Improved routing efficiency for half-day and weekly schedules.

Cost reduction while maintaining service quality.

Effective application of meta-heuristics to complex transportation problems.

Abstract

From 2010, the medical transport has become one of the top ten priorities of the risk management plan in France because of the increase in the cost. For social and medico-social institutions (MSI), this cost represents the second after that of the wages. In this context, the project NOMAd aims an overall improvement of the daily transport of people between their home and their (MSI). To this end, we propose the sharing of transport between several ESMS. This mutualization of transport makes possible to gather and optimize routes in a certain geographical area. The challenge is to improve economic performance while maintaining economic, social and environmental goals. From a scientific point of view, the studied problem is called the Time-Consistent-Dial-a-Ride Problem and aims to find a compromise between the objectives of the cost of transport and the consistency of the service. Given the complexity of the problem, we seek, first of all, to solve the problem for half a day. Then we consider the whole week. To solve these problems, we use the Large Neighborhood Search meta-heuristic and a master problem based on the Set Covering Problem.