D-Wave Implementation of Quantum Annealing for Optimal Resource Allocation in Disaster Response Operation of Marikina City
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Abstract
Quantum computing shows a positive approach for addressing optimization challenges in NP-hard problems such as the vehicle routing problem (VRP). This study focuses on improving the efficiency of disaster response operations by localizing the application of D-wave quantum annealing in Marikina City. This study uses the Solution Partitioning Solver (SPS) and the Quadratic Unconstrained Binary Optimization (QUBO) formulation to convert the VRP into an equation that can be solved using quantum annealing. The study demonstrates that quantum computing effectively distributes resources during emergency response operations and improves overall operational efficiency. In determining the most effective route for each vehicle, the D-wave Leap API and QUBO representation compute the distances traveled by each vehicle. These findings contribute to the practical applications of quantum computing to revolutionize various fields, including disaster management. Implementing D-wave quantum annealing in Marikina City shows relevance for future advancements in optimizing resource allocation and improving disaster response operations.
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