It is often very challenging to plan expedient and cost-effective operations for service trucks under network design constraints, particularly on congested urban roadways. Hence, it is beneficial to account simultaneously for decisions on truck facility location design and network expansion to mitigate the additional congestion caused by trucks and facilitate their routing. This study developed an integrated mathematical model for facility location design under network routing and congestion constraints. The model determines the optimal number and location of replenishment facilities, minimizes truck routing costs on the basis of proposed network design, assigns traffic in the network (for both general roadway users and service trucks), and selects candidate links for possible roadway capacity expansion. The model aims to minimize the total costs for new facility construction, truck routing, transportation infrastructure expansion, and transportation delay. A genetic algorithm framework was developed that incorporates a continuous approximation model for truck routing cost estimation and a traffic assignment algorithm. The numerical results show that the integrated solution technique can solve the problem effectively.
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