Fig 1.
Populations generated by the initialization of the good nodes set.
Fig 2.
Comparison of Common and the Proposed
.
Table 1.
Standard benchmark functions.
Table 2.
Running environment.
Table 3.
Parameter settings for metaheuristic algorithm.
Fig 3.
Iteration curves in ablation study.
Fig 4.
GWOA vs WOA flowchart.
Fig 5.
Results of the GWOA qualitative analysis (F1-F8).
Fig 6.
Results of the GWOA qualitative analysis (F9-F18).
Fig 7.
Results of the GWOA qualitative analysis (F17-f23).
Fig 8.
Iteration curves for comparison of different algorithms.
Table 4.
Ave and Std of different algorithms.
Table 5.
Results of Wilcoxon rank-sum test and Friedman test for different algorithms.
Table 6.
Wilcoxon Rank-sum Test and Friedman Test Results for Different Algorithms in 50 and 100 Dimensions.
Table 7.
Overall effectiveness of GWOA and other algorithms.
Fig 9.
The structure of a pressure vessel.
Fig 10.
Iteration curves in pressure vessel design.
Fig 11.
The structure of a tension/compression spring.
Fig 12.
Iteration curves in tension/compression spring design.
Fig 13.
The structure of a piston lever.
Fig 14.
Iteration curves in piston lever design.
Fig 15.
The structure of a speed reducer.
Fig 16.
Iteration curves in speed reducer design.
Table 8.
Results of the algorithms in solving engineering design optimization problems.
Table A1.
Details of the metaheuristic algorithms.
Table A2.
Details of parameter settings.