Topology-informed resource allocation for infrastructure systems: integrating network clustering and exact optimization
| Effective resource allocation and quantification of its benefits are essential in practical engineering problems. However, determining the allocation and location of resources is computationally challenging when dealing with large, interconnected systems, as is the case of infrastructure networks. We address the allocation and location of different types of resources to a set of potential sites in an infrastructure system, aiming to satisfy service demands at a minimum cost (e.g., in the context of disaster preparedness). Exact optimization methods become impractical for realistic network sizes, whereas fully heuristic approaches lack optimality guarantees. We use exact optimization to solve a heuristically pre-processed version of the resource location/allocation problem, which incorporates constraints that capture topological network properties based on community detection algorithms. Adding topological constraints leads to significant reductions in computation time without considerable deviation from optimal solutions, as community detection mostly forbids solutions that are unattractive in terms of network topology. The proposed approach to resource allocation incorporates a novel way to account for infrastructure network configurations within linear programming, leading to computational efficiency while producing solutions that capture the inherent topological properties of the network. |  |
Contact: Camilo Gomez
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