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20242026
most citedQuantum Relaxation for Solving Multiple Knapsack Problems

5 citations · 8 across the 12 of their papers we have counts for

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quant-ph2026

From Circuits to Hardware: Benchmarking Standard and Qubit-Efficient Quantum Optimization on Real Hardware

Monit Sharma, Hoong Chuin Lau

Despite rapid progress in quantum optimization, broad real-hardware benchmarks comparing multiple algorithmic families across diverse combinatorial problems under a common protocol…

quant-ph2026

Qubit-Scalable CVRP via Lagrangian Knapsack Decomposition and Noise-Aware Quantum Execution

Monit Sharma, Hoong Chuin Lau

Hybrid quantum optimization for vehicle routing faces a practical bottleneck: direct QUBO encodings of CVRP quickly exceed near-term qubit and gate budgets, while quantum evaluatio…

quant-ph2026

AutoQResearch: LLM-Guided Closed-Loop Policy Search for Adaptive Variational Quantum Optimization

Monit Sharma, Hoong Chuin Lau

Configuring variational quantum algorithms for combinatorial optimization remains a difficult, expert-driven process requiring coordinated choices over solver family, ansatz, objec…

quant-ph2025

Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning

Monit Sharma, Hoong Chuin Lau

Equivariant quantum circuits (EQCs) parameterise reinforcement-learning policies for combinatorial optimisation with a size-independent parameter count, suggesting policies trained…

quant-ph2025

Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks

Monit Sharma, Hoong Chuin Lau

Constraint handling remains a key bottleneck in quantum combinatorial optimization. While slack-variable-based encodings are straightforward, they significantly increase qubit coun…

quant-ph2025

Adaptive Graph Shrinking for Quantum Optimization of Constrained Combinatorial Problems

Monit Sharma, Hoong Chuin Lau

A range of quantum algorithms, especially those leveraging variational parameterization and circuit-based optimization, are being studied as alternatives for solving classically in…

quant-ph2025

A Comparative Study of Quantum Optimization Techniques for Solving Combinatorial Optimization Benchmark Problems

Monit Sharma, Hoong Chuin Lau

Quantum optimization holds promise for addressing classically intractable combinatorial problems, yet a standardized framework for benchmarking its performance, particularly in ter…

quant-ph2024

Quantum Monte Carlo methods for Newsvendor problem with Multiple Unreliable Suppliers

Monit Sharma, Hoong Chuin Lau

In the post-pandemic world, manufacturing enterprises face increasing uncertainties, especially with vulnerabilities in global supply chains. Although supply chain management has b…

quant-ph2024★ 5 cited

Quantum Relaxation for Solving Multiple Knapsack Problems

Monit Sharma, Yan Jin, Hoong Chuin Lau +1

Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variationa…

quant-ph2024★ 3 cited

Quantum-Enhanced Simulation-Based Optimization for Newsvendor Problems

Monit Sharma, Hoong Chuin Lau, Rudy Raymond

Simulation-based optimization is a widely used method to solve stochastic optimization problems. This method aims to identify an optimal solution by maximizing the expected value o…