This is a simple evolutionary algorithm. Each iteration of the loop randomly permutes the initial conditions of a function, and updates the initial conditions for the next iteration with the best solution found thus far.
To avoid falling into local optimal cycles, I would like the algorithm to reject solutions that are equal to any 3 previous (or n previous) solutions.
How do I create such a list?
for j in range(0, its+1):
# Seed initial conditions with best condition thus far.
k2, candidate1, candidate2 = k1, best_cond1, best_cond2
# Choose random nodes to swap from current conditions.
rand_node1, rand_node2 = choice(best_cond1), choice(best_cond2)
# Swap the nodes to create new candidate lists.
# Calculates a solution given the new conditions.
k2 = cost(candidate_list1, candidate_list2)
if k2 < k1:
k1, best1, best2 = k2, candidate1, candidate2
You can do something like this:
last_three =  for j in range(1, its + 2): ... k2 = cost(candidate1, candidate2) if k2 in last_three: continue elif k2 < k1: ... last_three[(j%3)-1] = k2
I had to change the loop to start at
1 in order to do the