Algorithm 1.

GeneticAlgorithm()

1	begin
2	Generate initial population of policies;
3	while stopping criteria not met do
4	foreach policy Ki do
5	Use Rinott method to determine sample size, Ni, for desired P(CS);
6	Simulate policy using determined sample size;
7	Record J(Ki);
8	end
9	BestPolicy ← policy with greatest expected QALYs;
10	Jmax ← J(BestPolicy);
11	foreach policy Ki do
12	if J(Ki) ≠ Jmax then
13	Parent1 ← TournamentSelect();
14	Parent2 ← TournamentSelect();
15	NewPolicy ← Crossover(Parent1, Parent2);
16	NewPolicy ← Mutate(NewPolicy);
17	Di ← NewPolicy;
18	end
19	end
20	end
21	return BestPolicy;
21	end