Car sharing is a concept that allows individuals to borrow cars on a short-term basis from a designated area or parking station, for a rental rate charged by the time or the distance driven. Many car sharing programs, such as ZipCar in London, involve electric vehicles in their car sharing fleets. The development of electric car sharing programs in densely populated cities may have many positive impacts such as a reduced urban congestion, less greenhouse gas emissions and a better air quality.
However, building a successful car sharing program is particularly challenging. It namely requires an adequate planning of the system operations to ensure both customer satisfaction and economic viability of the project. To satisfy potential customers, the car sharing operator should offer trip service joining as many locations as possible at an affordable price and ensure car availability at the right location and the right time.
In this project, the focus will be on the strategic long-term design of a one-way station-based electric car sharing network. In such a system, the user is required to pick-up the car at one of the stations of the car sharing network and return it to a station that may differ from the pickup one. We will thus seek to determine the optimal location and size of the stations, together with the number of vehicles in the fleet. To be practically relevant, these strategic decisions should be made while considering several important operational aspects of the problem such as the spatiotemporal distribution of the demand, the rebalancing of the cars between stations and the charging of cars.
Using a representation as accurate as possible of all the operational aspects related to the management of an electric car sharing network in the strategic design problem ensure that the obtained network, when deployed, has an actual performance close to the expected one. However, the resulting mathematical programming model is likely to be computationally intractable, even for medium-size instances, due to the huge number of variables and constraints involved in the formulation. Research is thus needed to identify which operational aspects should be modeled with a great level of accuracy in the strategic design problem and which ones can be overlooked or simplified without deteriorating the quality and practical relevancy of the network proposed by the optimization model.
Moreover, the problem involves significant uncertainties on its input parameters, which may have a strong impact on the EV sharing infrastructure. On the one hand, it is difficult to accurately predict the demand for shared car trips both in terms of flow volume and geographical distribution of this flow. On the other hand, the driving duration and electricity consumption on a given trip are subject to uncertainties, which may affect vehicle availability in the right area and the right time with the right battery level. Assessing the impact of these uncertainties requires the development of stochastic programming models and the implementation of appropriate solution methods.
The main objective of this project will be to develop a decision-aid tool based on mathematical optimization to help decision-makers optimally design an EV sharing network. The focus will be on the following:
– Modeling of the strategic planning problem taking into account the operational aspects of EV sharing
– Modeling of a stochastic version of the problem considering parameter uncertainties
– Development of efficient solution methods for the stochastic problem
Environment: The work will take place at the College of Business and Economics of the United Arab Emirate University located in the city of Al Ain in the United Arab Emirates. It will be jointly supervised by Dr. Mouna Kchaou Boujelben, Associate Professor at UAE University and Dr. Céline Gicquel, Associate Professor at the University of Paris Saclay.
Time and duration: The start of the project is expected to beginning of September 2023. The expected duration is 1 year.
Salary and other advantages: The postdoc will be offered an attractive salary, health insurance, round-trip ticket to the country of origin and 1 month paid vacation.
Profile of Candidates: Candidates must have a PhD in operations research, industrial engineering, or a related field. They must have a solid background in computer science, good programming skills, and a particular liking for operations research.
Contact: Candidates must send their CV, cover letter and any additional material that support their applications (such as recommendation letters and published journal or conference articles) to Dr. Mouna Kchaou-Boujelben (firstname.lastname@example.org) and Dr. Céline Gicquel (email@example.com).