Research Article
A Modified Bat Algorithm for Solving Large-Scale Bound Constrained Global Optimization Problems
Algorithm 1
Algorithm 1: Framework of the proposed modified Bat algorithm.
| (1) | : population size; | | (2) | : number of decision variables | | (3) | : maximum Iteration. | | (4) | : random number, : maximum Iteration. | | (5) | Initialize bat the population , | | (6) | Compute , , | | (7) | Find the current best | | (8) | | | (9) | while it ≤ Mitdo | | (10) | Generate new solution by flying randomly. | | (11) | | | (12) | | | (13) | | | (14) | | | (15) | | | (16) | Compute the objective function value, | | (17) | ifthen | | (18) | Accept . | | (19) | else | | (20) | Retain | | (21) | end if | | (22) | Update current best solution denoted by . | | (23) | Move the bats around current best solution randomly. | | (24) | | | (25) | Repeating steps 11 to 15 and update the global best solution. | | (26) | ; | | (27) | end while |
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