Leveraging the current generation of quantum devices to solve optimization problems of practical interest necessitates the development of hybrid quantum-classical (HQC) solution approaches. In this paper, a multi-cut Benders decomposition (BD) approach that exploits multiple feasible solutions of the master problem (MP) to generate multiple valid cuts is adapted, so as to be used as an HQC solver for general mixed-integer linear programming (MILP) problems. The use of different cut selection criteria and strategies to manage the size of the MP by eliciting a subset of cuts to be added in each iteration of the BD scheme using quantum computing is discussed. The HQC optimization algorithm is applied to the Unit Commitment (UC) problem. UC is ...
In this thesis, we aim to answer one research question: What is the algorithmic role of classical co...
Quantum variational circuits have gained significant attention due to their applications in the quan...
Quantum Approximation Optimization Algorithm (QAOA) is a highly advocated variational algorithm for ...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Mixed Integer Linear Programming (MILP) can be considered the backbone of the modern power system op...
Quantum algorithms for unconstrained optimization problems, such as the Quantum Approximate Optimiza...
Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy mar...
Increasing the size of monolithic quantum computer systems is a difficult task. As the number of qub...
Mixed Integer Programs (MIPs) model many optimization problems of interest in Computer Science, Oper...
In this thesis, we aim to answer one research question: What is the algorithmic role of classical co...
In this thesis, we aim to answer one research question: What is the algorithmic role of classical co...
Quantum variational circuits have gained significant attention due to their applications in the quan...
Quantum Approximation Optimization Algorithm (QAOA) is a highly advocated variational algorithm for ...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Leveraging the current generation of quantum devices to solve optimization problems of practical int...
Mixed Integer Linear Programming (MILP) can be considered the backbone of the modern power system op...
Quantum algorithms for unconstrained optimization problems, such as the Quantum Approximate Optimiza...
Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy mar...
Increasing the size of monolithic quantum computer systems is a difficult task. As the number of qub...
Mixed Integer Programs (MIPs) model many optimization problems of interest in Computer Science, Oper...
In this thesis, we aim to answer one research question: What is the algorithmic role of classical co...
In this thesis, we aim to answer one research question: What is the algorithmic role of classical co...
Quantum variational circuits have gained significant attention due to their applications in the quan...
Quantum Approximation Optimization Algorithm (QAOA) is a highly advocated variational algorithm for ...