![\"Computaci\u00f3](\"https:\/\/ignasisayol.com\/wp-content\/uploads\/2026\/06\/Computacion-cuantica-y-logistica.jpg\")
<\/p>\nFor years, quantum computing has existed in an uncomfortable space between fascination and exaggeration. For some, it is the next great technological revolution; for others, it is a promise too distant to deserve much attention. The truth, as is often the case with important technologies, lies somewhere in the middle: we are not dealing with science fiction, but neither are we facing a tool that will transform logistics overnight. What matters today is not waiting for miracles, but clearly understanding what quantum computing can contribute, what kinds of problems it could help solve, and how companies should prepare realistically.<\/p>\n
<\/p>\n
To begin with, it is worth explaining what quantum computing is without turning it into a spectacle. Classical computing \u2014 the kind that supports our ERPs, TMS, WMS and planning systems, \u00a0works with bits that take values of either 0 or 1. Quantum computing works with qubits, which can represent combinations of states thanks to properties such as superposition and entanglement. This does not mean that it magically \u201ctests all solutions at once,\u201d but it does mean that it can structure certain problems in a very different way from traditional computing. It is also important to remember that today\u2019s quantum computers are still rudimentary and prone to errors, and that they will not replace classical computers, but will most likely work alongside them.<\/p>\n
Google\u2019s Quantum Computer Achieves Quantum Supremacy Again – <\/strong>https:\/\/www.youtube.com\/shorts\/gH4SsABvqP0<\/a><\/p>\n <\/p>\n Because logistics is full of problems where the number of possible combinations grows extremely quickly. We are not only talking about \u201cmoving goods from point A to point B,\u201d but about deciding routes with constraints related to time, capacity, cost, priority, traffic, emissions, fleet availability, delivery windows and last-minute changes. On top of this, there are decisions involving network design, hub location, inventory allocation, vehicle loading, operational sequencing and resource planning. A recent academic review on quantum computing in logistics and supply chain summarizes this map of applications precisely: routing, logistics network design, fleet optimization, cargo loading, prediction, inventory management and operational scheduling.<\/p>\n Nor should we forget one of the most promising applications: the Physical Internet. This revolutionary model seeks to apply the logic of digital networks, sending goods in standardized, shared containers as if they were data packets, to create a hyperconnected global network capable of eliminating empty routes and drastically reducing emissions. I have written about this fascinating paradigm in previous articles available on my website.<\/p>\n Classical Computing vs. Quantum Computing<\/p>\n This is where the truly useful difference between classical and quantum computing applied to supply chain appears. Classical computing will continue to be excellent for executing operations, processing transactions, automating flows and solving a large part of everyday problems with heuristics, advanced optimizers and artificial intelligence. Quantum computing is not here to replace that operational muscle. In the best-case scenario, it will become an accelerator for certain classes of extremely complex problems, especially those involving combinatorial optimization and advanced simulation.<\/p>\n Microsoft puts it very clearly: in practice, quantum computing is hybrid; in other words, it combines classical and quantum processing within the same architecture.<\/p>\n How Amazon Plans To Catch Google And Microsoft In The Quantum Computing Race – <\/strong>Why does all this matter in logistics?<\/h2>\n