Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

Data: initial iterate, x0, initial temperature, T0, change bounds on x, ∆x,
algorithm parameters, ka, kr, kc, ndof
Result: optimal design variables and cost: x ∗ , J ∗
begin
Evaluate initial cost: J0 = f (x0)
Initialize: x = x0, J = J0, k =1,T = T0, A = R =0
while not frozen and number of function evaluations < max do
Randomly choose design variables to change based on ndof
Generate random change with bounds ∆x [Equations 2.42 and 2.43]
if xk is feasible then
Evaluate new cost, Jk = f (xk)
Calculate change in cost, ∆J = Jk − Jk−1
if ∆J kr or A>kA then
Increment temperature [Equation 2.45]
Reset counters, A = R =0
end
end
end
Return lowest-cost design: J ∗ =minJ, x ∗ =argminJ (x)
end
Figure 2-4: Simulated annealing algorithm.
58