IMRT

Optimization Algorithms

• Optimization algorithms find a solution by minimizing a function. • Virtually all algorithms use gradient information for the downhill search. • The size of the optimization problem limits the number of available algorithms to quasi-Newton methods and Conjugate Gradient search . If implemented well, none should be superior to the others. • These algorithms are deterministic, so that given infinite time, they find a minimum, which is unique in the absence of delivery constraints. • Some delivery constraints make the problem virtually unsolvable. • If nothing else helps: stochastic algorithms (like Simulated Annealing) which perform a sparse, random search of the entire solution space (which is very, very big). Stochastic algorithms are the last resort when the problem is otherwise intractable.

ESTRO IMRT course 2015 IMRT optimization: algorithms&cost functions Brussels October 5th, 2015

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