Geodesy

Whale

Algorithm

Benchmark (surveying)

Control (management)

Temperature control

Process (computing)

Engineering

Biology

Optimization algorithm

Multi-swarm optimization

Control engineering

Fishery

Operating system

Particle swarm optimization

Computer science

Mathematical optimization

Swarm behaviour

Swarm intelligence

PID controller

Mathematics

Geography

Artificial intelligence

Control theory (sociology)

Expert Systems with Applications

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.

IWOSSA: An improved whale optimization salp swarm algorithm for solving optimization problems