Goal

The research project considers the integrated cost and resource allocation between different logistics service providers in the tactical planning of city logistics. As a problem setting, a two-tier city logistics system is assumed where logistics service providers transport their goods from outside the city to so-called micro-depots from where smaller vehicles, e.g. cargo bicycles or electric vehicles perform the final delivery.

In a first step, a mathematical decision model (mixed-integer linear program) is developed to divide and allocate the resources (e.g., vehicles or micro-depot capacities). This model allows considering different scenarios that depend on the degree of resource sharing. Based on the resource allocation, we solve the cost allocation problem by adapting, applying, and comparing different concepts (e.g., Shapley value, proportional allocation).

To efficiently solve the modeled problem settings, we develop two heuristic methods. For the resource allocation problem, we develop a neighborhood-based search method (metaheuristic) that uses the underlying problem structure. For the integrated cost and resource allocation, we develop an integrated general framework. This framework can use the developed metaheuristic to solve the resource allocation problem as a subproblem. Due to its generic choice, the framework can be easily adapted to other cost allocation problems by exchanging the subproblem and therefore provides a general solution framework for complex cost allocation problems.

To evaluate the methods a general instance generator for city logistics problem settings is developed. This generator uses existing real data and can be used for other research projects and allows to compare different solution methods.

The project is funded by the German Research Foundation (DFG: Deutsche Forschungsgemeinschaft).