Towards scalable quantum annealing for pooling and blending problems: A methodological proof-of-concept

Industrial optimization challenges, such as the pooling and blending problem (PBP), require advanced computational methods to address non-convexity and scalability limitations in classical solvers. This work introduces a novel methodological framework for solving PBPs using quantum annealing (QA) th...

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Vydané v:Chemical engineering research & design Ročník 221; s. 560 - 576
Hlavní autori: Mappas, Vasileios K., Dorneanu, Bogdan, Nolasco, Eduardo, Vassiliadis, Vassilios S., Arellano-Garcia, Harvey
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.09.2025
Predmet:
Bilinear programming
Pooling/blending problem, Quadratic unconstrained binary optimization (QUBO) problem formulation
Quantum annealing
Pooling/blending problem, Quadratic unconstrained binary optimization (QUBO) problem formulation
Quantum annealing
Bilinear programming
ISSN:0263-8762
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Popis
Shrnutí:Industrial optimization challenges, such as the pooling and blending problem (PBP), require advanced computational methods to address non-convexity and scalability limitations in classical solvers. This work introduces a novel methodological framework for solving PBPs using quantum annealing (QA) that transforms the PBP into quadratic unconstrained binary optimization (QUBO) formulations at two resolution levels, enabling direct deployment on quantum annealers. Key innovations include a discretization technique tailored for PBP’s bilinear constraints and an embedding method optimized for current quantum hardware. Benchmarking against classical solvers focuses on Haverly’s classical three-stream PBP, enabling transparent comparison and development of quantum embedding and solution techniques. The proposed framework offers a scalable template for adapting similar engineering systems to quantum annealing architectures. Addressing genuine industrial-scale instances will require future advances in quantum hardware and embedding algorithms. The results demonstrate that QA exhibits the best performance among the examined alternatives, providing foundational insights towards leveraging QA in Process Systems Engineering. [Display omitted] •Novel quantum annealing approach for solving pooling and blending problem.•Proposed transformation procedure suitable for quantum annealers.•Tailored discretization and embedding optimized for current quantum hardware.•Scalable template for adapting engineering problems to quantum annealing.•Quantum annealing is a promising alternative as a solution approach.
ISSN:0263-8762
DOI:10.1016/j.cherd.2025.08.031