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IWOSSA: An improved whale optimization salp swarm algorithm for solving optimization problems
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AI
DOI：10.1016/j.eswa.2021.114901.png)
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摘要
En 中文
In this paper, a hybrid improved whale optimization salp swarm algorithm (IWOSSA) is proposed. The main idea behind IWOSSA is to combine improved Whale Optimization Algorithm (IWOA) and Salp Swarm Algorithm (SSA). First, WOA algorithm is improved by applying exponential relationships instead of linear relationships. Then, the algorithm chooses between either IWOA or SSA depending on a specific condition. To validate the efficiency of the proposed algorithm, IWOSSA is applied to 23 different benchmark functions of different dimensions and results are compared with 8 optimization algorithms including WOA and SSA. As an application to an industrial process and to confirm the good performance of the suggested algorithm, they are applied to tune an adaptive PID controller. The PID controller is used in controlling a divided wall column. Different disturbances are applied. From the simulation results, the enhancement made by the IWOSSA is proved by means of the different performance indexes.
Keyword:
MOTH-FLAME OPTIMIZATION
POWER POINT TRACKING
GENETIC ALGORITHM
INSPIRED ALGORITHM
BAT ALGORITHM
CONTROLLER
SYSTEMS
PSO