Application of Improved Multiverse Algorithm to Large Scale Optimization Problems

To overcome the mechanism shortcomings of wormhole and white hole selection in the Multi-Verse Optimizer (MVO), an Improved Multi-Universes Optimization (IMVO) algorithm is proposed. To speed up global exploration ability and quick iteration ability, this thesis designs the existence mechanism of wormhole with fixed probability and the Travel Distance Rate (TDR) that its convergence from early stage's smoothly to later stage's fast. The random white hole selection mechanism is proposed; Black holes can revolve around selected white hole stars and is modelled to solve the problem of information communication of the Inter-generational Universes. The performance of IMVO is verified by comparison experiments in low-middle dimensions. Three benchmarks test functions are selected for comparison in large scale which are difficult to be optimized, the experimental results show that IMVO has good applicability and robustness with higher solving accuracy and success rate in large scale optimization problem.