BMW Supply Chain

In an effort to find greater efficiency within its global supply chain, BMW has teamed up with Entropica Labs, a Singapore-based quantum software startup, to use the Honeywell System Model H1 quantum to computer. The aim of the undertaking is to examine supply chains and logistics for BMW and, “to investigate the transformative potential of quantum computing on the automotive industry,” according to Julius Marcea, head of IT, region Asia-Pacific, Eastern Europe, Middle East, and Africa, for the BMW Group.

BMW’s goal in embracing quantum computing is to eventually use it to make complex logistical decisions. A rudimentary example would be that one supplier may be able to deliver a given part or component faster than another, who is offering it at a lower price. Honeywell’s H1 computer can be used to determine the optimal choice, a process that would be incredibly taxing for a traditional or so-called “classical” computer like the kind many of us use on a daily basis.

Entropica Labs used the Recursive Quantum Approximate Optimization Algorithm (R-QAOA), which is described as a, “classic combinatorial problem that is an entry point to many logistics and supply chain problems of industrial interest,” according to Honeywell. The results were encouraging, with R-QAOA running on the H1 quantum computer outperforming simulations and brute force calculations.

Although largely preliminary and investigatory at this stage, the next step for BMW and Entropica is to explore more complex algorithms and to see if they can outperform the “classical” approach to logistical problem solving and decision making. Honeywell Quantum Solutions President Tony Uttley added that the project is an important step toward scaling up quantum technologies, and that, “We are quickly moving from benchmarking and double-checking data generated on quantum systems and algorithms to being able to tackle real-world, enterprise-level problems such as global supply chains.”—Alex Tock

BMW 5 Series G30 LCI

[Photos courtesy BMW AG.]



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