Research Article
A Novel Angular-Guided Particle Swarm Optimizer for Many-Objective Optimization Problems
Algorithm 3
The complete algorithm of AGPSO.
| (1) | Let t = 0, , initial particles , and T be the value of the neighborhood size | | (2) | for i = 1 to N | | (3) | randomly initialize position and set for | | (4) | evaluate the objective values of | | (5) | end for | | (6) | randomly initialize A with N new particles | | (7) | A = Angular-guided Archive update (S, A, N) | | (8) | sort A in ascending order based on equation (5) | | (9) | t = t + 1 | | (10) | while t < tmax | | (11) | calculate the SDE of each particle in S | | (12) | sort particles in S to get the medSDE | | (13) | Snew = Density-based Velocity Update (S, A, medSDE) | | (14) | A = Angular-guided Archive update (Snew, A, N) | | (15) | apply evolutionary search strategy on A to get a new swarm Snew | | (16) | evaluate the objectives of the new particles in Snew | | (17) | A = Angular-guided Archive update (Snew, A, N) | | (18) | sort A in ascending order based on equation (5) | | (19) | t = t + 2 | | (20) | end while | | (21) | output A |
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