Research Article
Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization
(1) Set the source position , produce new solution , maximum convergence iterations , current iteration . | (2) for (as a counter) from 1 to colony size | (3) calculate selective probability | (4) = rand() (as a random dimension of source position) | (5) = rand(1, colonysize) & (as another random dimension of source position) | (6) set | (7) if selective probability p > rand() | (8) for dim (as a counter) from 1 to max dimension | (9) new solution | (10) end for | (11) if new fitness value is better than fitness value | (12) then | (13) end if | (14) end if | (15) end for |
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