Problem Formulation (motivation, short- and long-term objectives, decision variables, control parameters, constraints);
Mathematical Modeling (representation of complex systems by analytical or numerical models, relationships between variables, performance metrics);
Data Collection (model inputs, system observations, validation, tracking of performance metrics);
Solution Methods (optimization, stochastic processes, simulation, heuristics, and other mathematical techniques);
Validation and Analysis (model testing, calibration, sensitivity analysis, model robustness); and
Interpretation and Implementation (solution ranges, trade-offs, visual or graphical representation of results, decision support systems).