Routing and logistics assignment problems grow combinatorially with every vehicle, time window, and resource limit added. Standard optimization tools handle the simple version well, but once the problem turns highly non-convex or mixes in genuinely discrete decisions, sequencing, assignment, routing order, they either take too long to run or settle for a plan far from the best one available.
We're developing exactly this today through QMIND, a public-private consortium funded by the Comunidad de Madrid, coordinated by GMV, working alongside BBVA, Repsol, and the CSIC. iQ Core works natively with the kind of variables that trip up conventional solvers instead of forcing awkward workarounds. This is still an emerging application for us, built in the open through this consortium rather than sold off the shelf. If you're facing exactly this kind of planning problem, we want to hear from you.
