MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123101 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy Engineering College For Women; Malla Reddy College Of Engineering And Technology; and Malla Reddy Vishwavidyapeeth, Medchal-Malkajgiri, Telangana, on Dec. 6, 2025, for 'quantum-driven operations optimization model for enterprise resource flow.'
Inventor(s) include Dr. K. Puspha Latha; Mr. Ayub Baig; Kkoushil Reddy; Mr. Thummapudi Venkata Seshu Kiran; Dr. M. Chalapathi Rao; and Dr. D. S. Chandra Mouli.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The current invention reveals a Quantum-Driven Operations Optimization Model (QDOOM) a new computational framework that will solve large-scale, problems that are combinatorial in nature in enterprise resource planning (ERP) and supply chain management in a manner never seen before at a break-even pace and with global optimality. Traditional classical methods of optimization (e.g. linear programming, heuristic search, mixed-integer programming) are based on iterative sequential algorithms. The number of variables and constraints of the modern global resource allocation, scheduling, and logistics networks are overwhelming to a point where these methods become computationally intractable, and thus companies are left to find sub-optimal heuristic solutions. The QDOOM breaks this intractability with the help of the special powers of quantum computing. The main invention of the QDOOM is a developed Quantum-Classical Hybrid Solver (QCHS). This solver consists of a Problem Mapping Module (PMM) to convert the multi-objective constraints of enterprise resource flow complexities (i.e. minimize cost and maximize speed of delivery and meet regulatory limits) into a format readable by quantum computers, namely the Quadratic Unconstrained Binary Optimization (QUBO) formulation. The PMM sources the big enterprise issue so intelligently, breaking it down into a solvable series of smaller, very complicated sub-problems that are outsourced to a quantum annealing or gate-based quantum processor. The solution makes use of Resource-Flow State Vector (RFSV) to model the entire enterprise system, in which the optimum resource path is sought. Using quantum phenomena such as superposition and entanglement, the QCHS uses the quantum processor to rapidly identify the global or nearly optimal solution to the sub-problems of the QUBO by solving all sub-problems simultaneously. These quantum outputs are in turn fed to a classical post-processing layer which in turn cues them back into the overall enterprise solution, which makes the QDOOM practical and scalable in heterogeneous corporate environments. The QDOOM allows the enterprises to gain global optimality in their scheduling, inventory management, and capital allocation by incorporating the exponential acceleration of quantum computation of the intractable parts of the optimization problem, which leads to the maximum efficiency, major reduction of costs, and greater responsiveness to market fluctuations. The system therefore is a radical change in the management of complex operational decisions. The structure also includes a Dynamic Constraint Translation Engine (DCTE). Given that operational limitations (e.g. fuel prices, availability of labor, regulatory changes) are continuously on the move, the DCTE will constantly modify the coefficients and penalty terms in the QUBO formulation in real time. This is to ensure that the quantum solver is continually optimizing with the present operational reality and not the previous one, which is needed to give real adaptive optimization capacity required by hyper-dynamic global supply chains."
Disclaimer: Curated by HT Syndication.
