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T. Jatschka, T. Rodemann, G. Raidl:
"VNS and PBIG as Optimization Cores in a Cooperative Optimization Approach for Distributing Service Points";
Talk: International Conference on Computer Aided Systems Theory (Eurocast), Las Palmas de Gran Canaria, Spain; 2019-02-17 - 2019-02-22; in: "EXTENDED ABSTRACTS-Computer Aided Systems Theory 2019", IUCTC Universidad de Las Palmas de Gran Canaria, (2019), ISBN: 978-84-09-09208-6; 70 - 71.

We consider a variant of the facility location problem [2]. The task is to find an
optimal subset of locations within a certain geographical area for constructing
service points in order to satisfy customer demands as well as possible. This
general scenario has a wide range of real-world applications. More specifically,
we have the setup of stations for mobility purposes in mind, such as constructing
bike sharing stations for a public bike sharing system, rental stations for car
sharing, or charging stations for electric vehicles.
A main challenge with such optimization problems is to come up with reliable
data for existing demand that may be fulfilled. Geographic and demographic
data is usually combined with the special knowledge of points of interest and
upfront surveys of potential users, but almost always this only yields a crude
estimate of the real existing demand and final acceptance of the system. Instead
of acquiring demand information from potential users upfront, we recently proposed
a cooperative optimization approach, in which potential users are tightly
integrated on a large scale in the optimization process [3]. For a more general
review on cooperative optimization methods see [5].
The method iteratively generates solution candidates that are presented to
users for evaluation. A surrogate objective function is trained by the users´ feedback
and used by an optimization core. The process is iterated on a large scale
with many potential users and several rounds until a satisfactory solution is
reached.

https://publik.tuwien.ac.at/files/publik_280735.pdf