Using Quantum Agents for Advanced Optimization Projects

10 million containers. Thousands of trucks. Hundreds of cranes. One impossible scheduling problem. Welcome to the Port of Los Angeles—the largest container port in the US and a critical node in global supply chains. The bottleneck: Every day, Pier 300 (one of the port's largest terminals) faces a computational nightmare: - Which truck goes to which crane? - When do arrivals shift due to delays? - How do you balance load across equipment? - What happens when conditions change every few minutes? Classical scheduling systems couldn't keep up: ⏱️ Long truck wait times (sometimes 2+ hours) 🏗️ Inefficient crane utilization 📉 Reduced throughput during peak periods 💰 Millions in lost productivity Then they deployed quantum optimization. Working with quantum computers, Pier 300 built a system that: 🔬 Simulates 100,000+ cargo-handling scenarios 🎯 Optimizes truck-to-crane assignments in real-time 🔄 Updates every few minutes across two daily shifts ⚡ Runs with 99.999% availability The results: ✅ ~40% reduction in crane usage → Lower labor and equipment costs ✅ ~60% increase in container deliveries per crane → Massive productivity gain ✅ 10 minutes reduced per truck visit → Up to 2 hours in some cases ✅ Tens of millions in annual savings → Plus increased terminal asset value Why this matters: This isn't theory. This is a working terminal processing millions of containers with measurable, bottom-line impact. The shift: From "schedule and hope" to "optimize continuously." Classical algorithms could generate a schedule. Quantum systems generate the optimal schedule—and update it dynamically as reality changes. The insight for supply chain leaders: Port operations are some of the most complex scheduling challenges on the planet. If quantum optimization can handle this, what could it do for your: 📦 Warehouse operations? 🚚 Fleet routing? 📊 Inventory allocation? 🏭 Production scheduling? The computational barrier just fell. The logistics advantage is here. Question: What's the biggest bottleneck in your logistics operations that classical optimization can't crack? #QuantumComputing #Truckl #SupplyChain #Transportation #Innovation

In a new preprint, researchers at Kipu Quantum introduce BBB-DCQO, a hybrid quantum algorithm tailored for solving higher-order unconstrained binary optimization (HUBO) problems. By combining bias-field digitized counterdiabatic quantum optimization with a branch-and-bound strategy, BBB-DCQO effectively explores complex solution spaces. BBB-DCQO was experimentally validated on IBM Heron QPU and benchmarked on 100-qubit HUBO instances—outperforming both simulated annealing and quantum annealing. It reached higher-quality solutions with up to 10x fewer function evaluations, and directly handles HUBO without the usual QUBO mapping overhead. This is another step toward practical, scalable quantum optimization with today’s hardware. Read the paper: arxiv.org/abs/2504.15367

One of the first papers in the World to outline quantum and agentic AI? This paper explores the intersection of quantum computing and agentic AI by examining how quantum technologies can enhance the capabilities of autonomous agents, and, conversely, how agentic AI can support the advancement of quantum systems. We analyze both directions of this synergy and present conceptual and technical foundations for future quantum-agentic platforms. Our work introduces a formal definition of quantum agents and outlines potential architectures that integrate quantum computing with agent-based systems. As a proof-of-concept, we develop and evaluate three quantum agent prototypes that demonstrate the feasibility of our proposed framework. Furthermore, we discuss use cases from both perspectives, including quantum-enhanced decision-making, quantum planning and optimization, and AI-driven orchestration of quantum workflows. By bridging these fields, we aim to chart a path toward scalable, intelligent, and adaptive quantum-agentic ecosystems. Eldar Gunter Sultanow, Dr. Mark Tehrani, Siddhant Dutta, Muhammad Shahbaz Khan https://lnkd.in/eDDmTWtQ

🚀 New blog post on the AWS Quantum Computing blog: Quantum-guided cluster algorithms for combinatorial optimization, the result of a collaboration between BMW Group, Siemens, Technical University of Munich, the Institute of Science and Technology Austria and Amazon Web Services (AWS). The post explores how correlations derived from quantum approaches can be used to guide cluster updates in classical optimization workflows, improving exploration of solution spaces compared to standard heuristics. Instead of changing one thing at a time, the algorithm learns which things tend to move together and updates them as a group. Worth a read if you’re interested in hybrid quantum-classical methods and practical paths toward optimization problems in areas like scheduling, routing, and network design. 👍 Great work by Peter J. Eder, Aaron Kerschbaumer, Christian Mendl, Jernej Rudi Finžgar, Helmut G. Katzgraber, Martin Schuetz, Raimel A. Medina and Sarah Braun https://lnkd.in/gchXgHgs #QuantumComputing #Optimization #HybridAlgorithms #AWS