The Problem

Industries often face complex decision-making problems involving the optimization of resources, scheduling, logistics, production planning, and more. Mathematical programming algorithms can propose solutions that optimize specific objectives, such as minimizing costs, maximizing efficiency, or meeting production deadlines. Industries like manufacturing, transportation, telecommunications, energy, and logistics extensively utilize optimization techniques to improve operations and achieve better outcomes.

Based on our experience in the development of optimization services over the last 7 years for EU companies, under both private consulting and EU-funded research projects, in industries such as metal fabrication, gearmotors, textile, oil, chemicals, intermodal/multimodal/city transportation, we have noticed the optimization solutions and techniques offered for industrial application are failing at multiple levels, e.g.,: they involve manual processes, are highly customized, do not preassume organization, automation and standardization of input data, do not prove provide performance guarantees, are not easily parameterized to extract managerial insights, they do not interact with other technologies (ML and simulation tools).