Swarm-Intelligence Optimization Method for Dynamic Optimization Problem

In recent years, the vigorous rise in computational intelligence has opened up new research ideas for solving chemical dynamic optimization problems, making application of swarm-intelligence techniques more and widespread. However, potential algorithms with different performances still needs to be further investigated this context. On premise, paper puts forward a universal framework, which transforms infinite-dimensional problem into finite-dimensional nonlinear programming through control variable parameterization. order improve efficiency accuracy optimization, an improved version multi-strategy enhanced sparrow search algorithm is proposed from side, including good-point set initialization, hybrid strategy, Lévy flight mechanism, Student’s t-distribution model. The resulting augmented theoretically tested on ten benchmark functions, compared whale algorithm, marine predators harris hawks social group basic statistical results verify that advantages most tests. Finally, six are applied three typical problems under framework. achieves optimal higher than methods other references.