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A Cooperative Optimization Approach for Distributing Service Points in Mobility Applications

Thomas Jatschka, Tobias Rodemann, Guenther Raidl, "A Cooperative Optimization Approach for Distributing Service Points in Mobility Applications", EvoCOP, pp. 1-16, 2019.


We investigate a variant of the facility location problem concerning the optimal distribution of service points with incomplete information within a certain geographical area. The application scenario is generic in principle, but we have the setup of charging stations for electric vehicles or rental stations for bicycles or cars in mind. When planning such systems, estimating under which conditions which customer demand can be fulfilled is fundamental in order to evaluate possible solutions and optimize. In this paper we present a cooperative optimization approach for distributing service points that incorporates potential customers not only in the data acquisition but also during the optimization process. A surrogate objective function is used to evaluate intermediate solutions during the optimization. The quality of this surrogate objective function is iteratively improved by learning from the feedback of potential users given to candidate solutions. For the actual optimization we consider a variable neighborhood search and a population based iterated greedy algorithm as alternatives. Experiments on artificial benchmark scenarios show the learning capabilities of the surrogate objective function and the effectiveness of the optimization.

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