Our R&D team: Innovators in Operational Research and AI
Behind every breakthrough in Operational Research and Artificial Intelligence for route optimisation is a team of passionate experts. Our R&D team brings together specialists in mathematics, data science, AI and logistics to develop cutting-edge solutions that transform last-mile logistics. At AntsRoute, we tackle complex logistics challenges and push the boundaries of innovation.
About us : Meet our OR and AI experts
Our team includes researchers and engineers with expertise in machine learning, heuristic algorithms and dynamic route planning. We develop advanced optimisation solutions tailored to the requirements of the last mile.
Ammar Oulamara
Head of R&D
“As a teacher researcher at the University of Lorraine and co-founder of Antsway, I manage our R&D department and carry out innovative research to improve logistics and route planning.”
Olivier Hibon
Software Development Manager
“Since 2010, as Software Development Manager, I’ve been heading up the development team based in Angers, which consists of two R&D engineers specialising in route optimisation.”
Bilal Messaoudi
PhD in R&D
“As a PhD in R&D, I develop and optimise algorithms to improve the performance of our route management and optimisation software.”
Benoit Loger
PhD in R&D
“I’ve been an R&D Engineer in Angers for a year now. With a thesis in production management optimisation, I bring my expertise to the development of innovative solutions.”
Clément Besnard
R&D Engineer
“I analyse and use data to design and develop Artificial Intelligence systems for planning field service operations and deliveries, and optimising routes.”
Christophe Jayet
Technical Manager
“As Technical Manager, I define the software architecture, optimise performance and ensure compliance with best practice to ensure a reliable and scalable product.”
Laurent Girard
Product Manager
“As Product Manager, I drive the development of innovative solutions, combining business expertise and performance to meet users’ needs.”
Cédric Angellier
Analyst
“As an expert in route optimisation tools, I take part in transport plan studies.”
Guillaume Coste
Project Manager
“Thanks to my business expertise, I can help customers define constraints and optimisation objectives as part of their transport plans.”
Our mission
Our mission is to develop innovative, sustainable and cost-effective optimisation solutions for transport and logistics. By integrating artificial intelligence and operational research, we help companies to improve their performance while reducing their environmental footprint.
Our vision
Our vision is to anticipate future needs in logistics and develop technologies capable of adapting in real time to unforeseen events. Thanks to AI, we are aiming for more agile, efficient and environmentally-friendly logistics.
Our expertise in Operational Research and Artificial Intelligence
Mathematical optimisation in logistics
Our experts develop models based on advanced metaheuristic programming to solve complex optimisation problems in logistics.
We design bespoke algorithms to optimise dynamic route planning, reducing operating costs and delivery times while improving overall efficiency.
AI-based solutions
We use machine learning models to predict demand in real time, enabling optimum allocation of resources and better management of transport flows.
Our machine learning algorithms automatically optimise logistics fleets in line with operational constraints, reducing the number of kilometres travelled and increasing profitability.
Data-driven decisions
We analyse and process massive volumes of logistics data in real time to detect trends and improve strategic decision-making.
Using AI-assisted simulations, we test different optimisation scenarios, enabling companies to better anticipate variations in demand and adapt their strategies accordingly.
R&D innovations and achievements
Advances in route optimisation
Development of a system with AI capable of adapting routes according to actual traffic conditions and real-time delivery requirements.
Significant contributions to research into sustainable logistics, with the integration of algorithms to reduce the carbon footprint of fleets and optimise the use of electric vehicles.
Industrial collaborations and partnerships
We conduct joint research projects with universities and logistics companies to develop innovative technologies tailored to the challenges of the sector.
Frequently Asked Questions (FAQ)
Our team stands out for its expertise combining operational research, artificial intelligence and field experience. This approach enables us to design solutions that combine scientific rigour with practical applications in the field of logistics.
Thanks to our collaborations with industrial and academic partners, we are able to test our algorithms on real data, guaranteeing reliable and optimised solutions for companies in the sector.
We are committed to continuous improvement, incorporating the latest advances in machine learning to ensure greater competitiveness in the face of last-mile challenges.
We use machine learning to analyse huge datasets and identify demand trends, enabling us to anticipate transport needs and rationalise resources.
Our learning models enable dynamic route optimisation, taking into account traffic conditions, delivery constraints and changes in demand in real time.
Predictive analytics enables us to identify friction points before they become obstacles, providing companies with proactive solutions to minimise delays and improve customer satisfaction.
Thanks to these technologies, we offer customised and adaptive solutions, guaranteeing efficient and agile optimisation of logistics operations.
Absolutely! We actively collaborate with logistics companies, universities and industrial partners on innovation and research projects.
- Faster deliveries: AI can recalculate and adapt vehicle routes in real time, reducing journey times and ensuring faster delivery.
- Reduced operating costs: By optimising the use of resources, AI reduces unnecessary kilometres travelled and cuts fuel consumption, generating significant savings.
- Minimising environmental impact: Our AI solutions promote greener routes, limiting CO₂ emissions and encouraging sustainable logistics with better fleet management.
- Increased fleet efficiency: Thanks to intelligent algorithms, fleet management is optimised according to operational constraints, real-time traffic and delivery priorities.
- Improved customer experience: Better prediction of delivery times and optimised resource management contribute to greater customer satisfaction and loyalty.
Our AI models and OR techniques are designed to handle large datasets, ensuring that they are suitable for businesses of all sizes.
