As a part of the initiative to improve local air quality, cities have encouraged fleets of vehicles, in particular of taxicabs, to adopt alternative technologies like electric vehicles (EVs).

In this context, operators of EV charging infrastructure need to dimension their infrastructure and design charging tariffs. On their side, each taxicab company has to decide whether to pay for these services or not to adopt EVs.

The resulting problem can be modeled using mixed-integer nonlinear programming (MINLP). Thanks to its performance, Artelys Knitro was chosen among other off-the-shelf optimization solvers. It allows the authors of this article to derive insights on how problem parameters, such as service cost, taxicab companies’ fleet size and miles-driven, inconvenience cost for recharging EV batteries, impact the service provider’s profits and the participating set of taxicab companies.