Research Article
A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization
Algorithm 1
The standard bat algorithm.
| (1) | define objective function | | (2) | initialize the bat population and for k = 1, ⋯, n | | (3) | Define pulse frequency at . | | (4) | Initialize pulse rates and the loudness . | | (5) | While (t ≤ tmax). | | (6) | Adjust frequency equation (33) | | (7) | Update velocities equation (34) | | (8) | Update locations/solutions equation (35) | | (9) | if (rand > ) | | (10) | Select a solution among the best solutions | | (11) | Generate a local solution around the selected best solution equation (36) | | (12) | end if | | (13) | Generate a new solution by flying randomly | | (14) | if (rand < & F() < F()) | | (15) | Accept the new solutions | | (16) | Increase equation (37) | | (17) | Reduce equation (38) | | (18) | end if | | (19) | Rank the bats and find the current best | | (20) | end while | | (21) | Output results for post-processing |
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