A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm

Table 1

Problems solved by WOA.

Method	Year, references	Problem	Purpose	Conclusion
WOA for constrained economic load dispatch problems	2018, [13]	Economic load dispatch problem constraining	Giving reliable and constant electricity, whereas obtaining the best production with least cost and system operations	Solving the ELD problem resulted in the fast convergence and appropriate execution time
Binary WOA (bWOA)	2018, [14]	Dimensionality reduction and classifications problem	Selecting the optimal feature subset, which can be the optimal solution based on the sigmoid transfer function (S shape)	bWOA could find optimal features, which have vital performance in terms of accuracy and execution time
Multiobjective method for vehicle traveling based on WOA (MOWOA)	2017, [52]	Vehicle fuel consumption problem	Optimizing vehicle fuel consumption in terms of vehicle direction and traffic status	MOWOA satisfied the performance within the vehicle traveling optimization, and the performance increased slightly compared to Dijkstra’s and A algorithm
Using WOA	2018, [53]	Nonuniformity in speed communication and illumination	Optimizing the position of the light emitting diodes (LEDs)	The result showed that this approach has given the higher uniformity compared to another result achieved by PSO
MOWOA	2018, [54]	Multilevel threshold as a multiobjective function problem	Determining the multilevel threshold value for image segmentation	The result showed that WOA had better performance for solving this problem within faster convergence and lower execution time
Multiobjective task scheduling algorithm using WOA	2017, [15]	The multiobjective task scheduling problem	Availability of low cost for each service and minimizing the execution time	The result showed great improvement in the proposed algorithm compared to original WOA
Improved whale optimization algorithm (IWOA) for solving both single and multidimensional problems	2017, [55]	0–1 knapsack problem	Handling infeasible solutions are the aim of this modification by adding penalty function to the evaluation function and sigmoid function to take the input parameter, which is the real-valued, and then produce the output	IWOA is able to give a balance between exploration and exploitation by using local search strategy (LSS) and the Lévy flight walks. The result indicated that IWOA is robust, effective, and efficient for solving this problem compared to other metaheuristic algorithms, which were used to solve this problem
The time-optimal memetic whale optimization algorithm	2017, [56]	Hypersonic vehicle re-entry trajectory optimization problem with no-fly zones	Improving the robustness of IWOA to extend its strong ability on global search and improve the nonsensitivity of the initial values. Improve IWOA poor searching convergence speed by using Gauss pseudospectral methods (GPM)	Compared to the initial guess solution results of this hybridized technique, it concluded that it is very competitive and has better search accuracy, convergence speed, and robustness