Alternatives to evolutionary computing for structure, design and policy optimization (optimal structure search)?
At a broad level, there are two types of optimization: continuous optimization, and discrete optimization.  They tend to use different techniques.

Continuous optimization deals with problems where the parameters are continuous; methods include gradient descent, Newton's method, and other iterative methods, linear programming, and more.

Discrete optimization, or combinatorial optimization, deals with problems where the parameters come from a finite site; methods include integer linear programming, SAT, simulated annealing, particle swarm optimization, and more.

Genetic algorithms are another technique.  However, my experience is that they are rarely the best one; other methods often beat genetic programming and evolutionary optimization methods.  Your experience may vary.