Algorithm 3: Calculate the Entropy

Input:

N: The population size

N uniformly distributed weight vectors: ${\lambda }^1,\dots {\lambda }^N$

$rho$: the count of solutions associated with each reference point

Association:

1: Measure the distance between each solution and each reference vector: Cosine

2: Match each solution with its closest reference point: pi

3: Compute the count of solutions associated with each reference point: rho

Calculate the Entropy:

4: entropy = 0

5: i = 1

6: while $i\le N$ do

7: if $Num\left(i\right)\ne 0$, then $p=Num\left(i\right)/N$, entropy = entropy +$p\ast log\left(p\right)$

8: end

9: if the loop ends

10:  entropy = −entropy

11: end if

12: i = i + 1

13: end

Output:

entropy