D-Wave and Lockheed Martin Advance Quantum Route Optimization for Aerospace Logistics

Quantum Optimization Lands on the Tarmac

As the logistics industry expanded its digital transformation efforts in 2018, a quieter revolution was unfolding in the world of quantum annealing—a specialized branch of quantum computing suited to optimization problems.

D-Wave Systems, the Canadian quantum computing pioneer, had already delivered systems to several major institutions, including NASA, Google, and Lockheed Martin. But in January 2018, new details emerged about how Lockheed Martin was testing quantum annealing for air cargo and aerospace logistics optimization.

While D-Wave’s systems differ from universal quantum computers being pursued by IBM and Google, they excel at solving combinatorial optimization problems—precisely the type of challenge found in flight scheduling, route planning, and cargo loading.

The Lockheed-D-Wave Partnership Reaches a New Phase

Lockheed Martin became D-Wave’s first commercial customer in 2011 and had been steadily developing applications through its Advanced Technology Center (ATC) in Palo Alto. By January 2018, internal teams were focused on several aerospace logistics challenges:

• Air fleet maintenance scheduling

• Cargo space optimization

• Multi-stop route planning for supply aircraft

• Fuel-efficient cargo load balancing

The goal was to use quantum annealing algorithms to find near-optimal solutions faster than classical heuristics could—especially in real-time scenarios.

In an internal briefing made public through D-Wave’s corporate blog in January 2018, Lockheed engineers reported success in modeling certain logistics problems with binary quadratic models (BQMs) that mapped well to D-Wave’s quantum processing units (QPUs).

One example involved optimizing delivery routes for multiple cargo planes that needed to service remote military bases, with constraints on weather, fuel, payload, and airspace permissions. The quantum annealer was able to reduce computation time for viable solutions by up to 60% compared to classical algorithms in simulation.

Why Quantum Annealing Matters for Logistics

Unlike universal quantum computers, which manipulate qubits through entanglement and gate-based logic, quantum annealers use a process akin to energy minimization in a quantum system to find the best solution among a vast number of possibilities.

This makes them ideal for logistics applications such as:

• Traveling Salesman Problems (TSP)

• Job-shop scheduling

• Network flow optimization

• Real-time dynamic routing

For global air logistics providers—especially in the defense and aerospace sectors—these problems are mission-critical.

In January 2018, Lockheed’s ATC team revealed that they had developed a proprietary framework to translate logistics planning variables into quantum-compatible Hamiltonians—mathematical representations of energy landscapes solvable by D-Wave’s hardware.

Global Implications: A Quantum Advantage in Defense Logistics

While Lockheed Martin’s work is typically cloaked in secrecy, the implications for global defense logistics were clear. With increasing geopolitical volatility, military contractors are seeking faster ways to:

• Respond to natural disasters with airlifted aid

• Re-route aircraft in congested or contested airspace

• Pre-position supplies efficiently across continents

Using quantum optimization could shave precious minutes—or even hours—off critical logistics decisions.

In one January 2018 presentation to the U.S. Department of Defense logistics modernization group, Lockheed scientists shared quantum simulation benchmarks using D-Wave 2000Q hardware, showing performance improvements over classical solvers in routing and cargo alignment under real-world constraints.

Civil Aviation Applications Emerge

Though initially focused on defense, civil aviation logistics players began paying attention. According to sources in the International Air Transport Association (IATA), several working groups in early 2018 began analyzing quantum optimization as a future enhancement to:

• Airport slot allocation

• Gate scheduling

• Passenger-cargo balance optimization

• Route fuel efficiency under variable weather

A January 2018 paper presented at the American Institute of Aeronautics and Astronautics (AIAA) SciTech Forum by researchers from the University of Southern California’s Information Sciences Institute—which also houses a D-Wave system—proposed a quantum-assisted decision support tool for cargo route planning.

Their simulation results suggested that hybrid quantum-classical solvers could accelerate planning cycles for complex air logistics networks by up to 35%, with particular gains in scenarios involving disruption recovery (e.g., canceled flights, sudden demand surges).

Asia and Europe Watch Closely

In Japan, the National Institute of Informatics published a white paper in January 2018 outlining potential use cases for D-Wave-based quantum optimization in automated logistics hubs, including Narita and Kansai airports.

Meanwhile, Airbus, a D-Wave collaborator through its A3 innovation unit in Silicon Valley, began preliminary modeling of air cargo container configuration and route timing, according to internal discussions shared at the World Economic Forum in Davos, January 23–26, 2018.

In Germany, Lufthansa’s innovation arm issued a statement that same month confirming their exploration of quantum algorithms for ground operations logistics in collaboration with the Fraunhofer Society’s Quantum Computing Initiative.

These movements signal that quantum optimization for logistics was no longer purely speculative—it was an emerging area of R&D with international traction.

Technical Barriers and Hybrid Quantum-Classical Solvers

Despite these advances, limitations remained.

The D-Wave 2000Q, while powerful in specific problem domains, had architectural constraints: it could solve only certain problem types and required precise problem mapping to its Chimera graph topology.

To work around this, Lockheed and others increasingly adopted hybrid solvers—which offload part of the computation to classical processors and use the quantum annealer for rapid convergence.

In January 2018, D-Wave introduced updates to its Ocean SDK, enabling more streamlined development of these hybrid workflows. This paved the way for logistics applications that balanced quantum speedups with classical reliability, especially for mixed-integer optimization tasks.

Looking Ahead: Commercial Aviation and Beyond

The aerospace logistics sector now faces a convergence of needs:

• Faster reactivity to supply chain disruptions

• Optimized maintenance cycles

• Climate-conscious route planning

Quantum annealing could address each of these, especially as flight networks grow more complex and volatile.

With Lockheed Martin leading pilot tests, commercial aviation players began investigating partnerships. According to insiders at Boeing, internal studies were underway by Q1 2018 on quantum-enhanced design for flight path optimization under environmental constraints—with cargo efficiency as a secondary benefit.

Conclusion: Quantum Logistics Takes Flight

January 2018 marked a pivotal moment where aerospace logistics and quantum optimization formally began to intertwine. Lockheed Martin’s collaboration with D-Wave Systems transitioned from experimentation to practical logistics modeling, pushing quantum annealing into mission-critical applications.

The groundwork laid during this month—including simulation trials, hybrid solver development, and international interest—shows that quantum computing is becoming not just a research curiosity, but a potential operational tool in the global air cargo and aerospace supply chain.

As the race for quantum utility accelerates, those who invest early in route optimization, fleet planning, and supply scheduling may gain not just efficiency—but a strategic logistics advantage in the skies.