Mathematical Optimization Foundations

Turn an allocation question into an explicit model and a defensible solution claim. Separate a good candidate, a feasible candidate, and a certified optimum.

When to Use

Trigger: constrained allocation, linear programming, convex optimization, integer programming, duality certificates, optimality gaps, or robust/stochastic optimization.

Examples: allocate a fixed capacity across products; verify an LP primal/dual witness; choose a formulation for uncertain demand.

Use decision theory to choose preferences or utilities, planning/search for action sequences, and theory of constraints to identify where improvement should focus. This skill owns the mathematical allocation after those choices. Ordinary prioritization without a quantitative constrained model need not activate it.

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