A Hybrid Quantum-Classical Framework for Socioeconomically Weighted Warehouse Facility Location: Novel QUBO Formulation with Automated Repair Mechanisms and Theoretical Performance Guarantees
Year: 2025
Type: preprint
Abstract: This paper introduces a groundbreaking hybrid quantum-classical algorithm for the socioeconomically weighted warehouse facility location problem, addressing critical challenges in modern supply chain optimization. We present a novel Quadratic Unconstrained Binary Optimization (QUBO) formulation with rigorously derived penalty parameters, automated constraint repair mechanisms, and theoretically proven performance guarantees. Our hybrid approach integrates demand-weighted kmedoids clustering with quantum annealing, achieving an 7.92% reduction in total weighted distance over classical baselines while maintaining 95% feasibility rates. Key innovations include: (1) mathematically rigorous penalty parameter bounds ensuring constraint satisfaction, (2) automated quantum solution repair algorithms with bounded objective deterioration, (3) intelligent hybrid merging strategies leveraging complementary classicalquantum strengths, and (4) empirical 95% repair bound and a sufficient computable penalty condition. Experimental validation on real Hyderabad socioeconomic data demonstrates superior performance with approximation ratio 1.11 compared to pure quantum approaches (1.22) and classical methods (1.05), establishing practical quantum advantage for logistics optimization,
Author: Yalla Jnan Devi Satya Prasad
Language: English
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4414200132
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