Antioptimisation of Trusses Using Two-Level Population-Based Incremental Learning

Algorithm 1

Population-based incremental learning.

Initialisation 𝑃_𝑖=0.5,  𝑘=0,  𝐛= {⋅}

Main procedure

(1) Generate a binary population B according to 𝑃_𝑖.

(2) Perform function evaluations 𝑓(𝐁) and find the best

solution b from 𝐁∪𝐛.

(3) Update 𝑃_𝑖 using (5).

(4) Set 𝑃_𝑖 to [0.1,0.9] in cases that it is out of the interval.

(5) If the termination condition is met, stop the procedure;

otherwise, set 𝑘=𝑘+1 and go to (1).