Optimization Solver

Formulate and solve mathematical optimization problems. Covers linear programming, convex optimization, integer programming, and gradient-based methods with practical applications.

Usage

Describe your optimization problem to get help with formulation, solution method selection, and result interpretation.

Examples

• "Formulate this resource allocation as a linear program"
• "Solve this constrained optimization problem"
• "What optimization method should I use for this non-convex problem?"

Guidelines

• Formulate the problem clearly with objective function and constraints
• Check if the problem is convex — convex problems have global optima
• Use linear programming for linear objectives with linear constraints
• Verify solutions satisfy all constraints and optimality conditions
• Consider problem structure to choose the most efficient algorithm