The HOPES project funded by the ANR 2021 with 270 KE is led by a young researcher RESTREPO RUIZ Maria-Isabel on the planning of work schedules and employee rounds over a multi-period horizon for home-based services. HOPES will propose innovative decision support tools to solve these complex problems by taking into account work rules, individual preferences and different sources of uncertainty. To do so, we will rely on the formulation and design of new optimization approaches integrating techniques from data science and deterministic and stochastic optimization. Instead of proposing a method that works only for a specific application, HOPES aims to propose a general framework that can be extended to solve different variants of the problem. The decision support tools developed are expected to improve the quality of service for users, the well-being of employees, and to improve the planning and execution of home service operations.
Home service (HS) operations are becoming increasingly important due to social, demographic, and epidemiological trends in most countries. Home healthcare services (HHC), last mile delivery (LMD), and interventions of technicians at customers’ homes are some examples of HS operations. As reported in recent social and demographic studies, several service operations, which require customers to travel and to visit a place indoor, are switching to become services provided at home. Indeed, France has seen a considerable growth in HHC where home hospitalisation activity has more than doubled in ten years (ARS, 2018). These numbers could grow larger thanks to the 2016 loi de modernisation de la sante (DREES, 2019). This law aims at shifting some care services organised around the hospital to ambulatory care. Its objective is to reduce inequalities and to increase the quality of life for the patients, as they are allowed to remain at home where they are most comfortable. Moreover, it also yields relevant cost savings for the entire healthcare system as hospitalisation costs are avoided. The last mile delivery sector is not far behind, as from 2014 to 2019 e-commerce sales ratios nearly tripled globally (WEF, 2020). This accelerated growth creates important challenges and opportunities for HS providers and requires the development of decision support tools to optimise HS operations and to organise them in a more sustainable way.
HOPES is interested in four objectives:
- to improve the working conditions and well being of
- employees by assigning them to fair work schedules that respect working regulations;
- to avoid non executable and sub-optimal routing and scheduling plans by considering several decision levels in a joint way (e.g. tactical employee scheduling coupled with operational routing);
- to increase employee satisfaction by modelling and including employee preferences in the optimisation models;
- to face real-world uncertainty (e.g. in customer demands, in supply capacities) by including stochastic information in the optimisation models.
The project will be structured around five work packages (WP) as shown in the Figure below:
WP1: modelling and integrating multi-period regulations.
WP2: multi-period employee scheduling and routing with employee preferences.
WP3: multi-period employee scheduling and routing with uncertainty.
WP4: multi-period employee scheduling and routing with employee preferences and uncertainty.
WP5: use-case validation in collaboration with some industrial partners.
Polytechnique Montréal. Role: the Ph.D students involved in HOPES project will have a research stay in Montreal. Hence, the professor at Polytechnique Montreal will supervise them and this university will provide all the elements necessary for their stay.
- Projects’ coordinator: Maria Isabel RESTREPO RUIZ. Maître de conférences, IMT Atlantique.
- Permanent researchers :
- Odile BELLENGUEZ. Professor, IMT Atlantique.
- Guillaume MASSONET. Maître assistant, IMT Atlantique.
- Olivier PETON. Professor, IMT Atlantique.
- Ph.D. Students :
- Paul FLEURANCE. IMT Atlantique
- Guillaume GHIENNE. IMT Atlantique
External Collaborators :
Nadia Lahrichi. Associate professor. Polytechnique Montreal.
Dissemination of results
The results found in this project will be published in peer reviewed journals and presented in international conferences. The tools developed will be made publicly available for further exploitation and development of extensions.