The OPTIMAX Linear and Mixed Integer Programming Optimization Platform provides dedicated computational resources and professional-grade software tools for formulating, solving, and deploying complex mathematical optimization models. Built on high-performance multi-core CPU infrastructure and equipped with academic Gurobi licenses alongside open-source Python optimization libraries (including PuLP, OR-Tools, SciPy, and Pyomo), this testbed enables researchers and industry partners to tackle large-scale linear programming (LP), mixed integer programming (MIP), and combinatorial optimization problems. Application domains include supply chain optimization, resource allocation, scheduling, logistics, and energy systems planning. The environment supports the full optimization workflow, from problem formulation and model development through to solution analysis and deployment-ready implementations. This testbed contributes to the CITADELS Framework by providing accessible, state-of-the-art optimization capabilities relevant to Industry 5.0 challenges such as sustainable production planning, human-centric resource management, and data-driven operational decision-making.