What are the main challenges in conditional optimization?

What are the main challenges in conditional optimization?

Conditional optimization often faces challenges like non-convexity, high dimensionality, and the need for robust algorithms.

Can you explain non-convexity in this context?

Non-convexity refers to the presence of multiple local minima, making it difficult to find the global optimum.

How does high dimensionality affect optimization?

High dimensionality can lead to the curse of dimensionality, where the search space becomes exponentially larger and harder to navigate.

What are some robust algorithms used in conditional optimization?

Some robust algorithms include genetic algorithms, simulated annealing, and various gradient-based methods.