329. Chance Constraints

Constraints required to hold with high probability rather than always. Useful when:

329.1. Formulation

For uncertain parameters :

The constraint must hold with probability at least . is the risk level — typically or .

Equivalent: violate the constraint with probability at most .

329.2. Joint vs individual chance constraints

Individual: each constraint holds with high probability, separately:

Joint: all constraints hold simultaneously with high probability:

Joint is stronger — and harder to handle. Often individual is what’s actually intended.

329.3. Reformulation under normality

If is normally distributed (with mean and variance ):

The chance constraint becomes a deterministic constraint involving — possibly convex (e.g., if is linear in and ). This is a second-order cone constraint, solvable by interior-point methods.

329.4. Reformulation via sampling

Without normality, use scenarios :

Enforcing the chance constraint on the sample becomes an MILP with binary indicators per scenario — exponential growth, manageable up to .

329.5. Equivalence to VaR / CVaR

In risk management, chance constraints relate to:

In practice, CVaR-based reformulations of chance constraints are more numerically tractable.

329.6. Where chance constraints matter

329.7. See also