Table 41 Comparison of results for multi-pass turning process problem

From: Cohort intelligence with self-adaptive penalty function approach hybridized with colliding bodies optimization algorithm for discrete and mixed variable constrained problems

Variables GA
(Gayatri and Bhaskar [24] 		SA
(Gayatri and Bhaskar [24] 		PSO
(Gayatri and Bhaskar [24] 		HGSS (Gayatri and Bhaskar [24] CI–SAPF CI–SAPF–CBO
\({V}_{r}\) 389.15 447.94 499.99 499.9938 495.0761 496.0539
\({f}_{r}\) 0.7209 0.7255 0.8999 0.8939 0.1163 0.107
\({d}_{r}\) 2.03 2.21 2.50 2.50 2.4306 2.5186
\({V}_{s}\) 102.78 117.17 89.55 93.8986 144.0232 167.1331
\({f}_{s}\) 0.8788 0.5059 0.8999 0.8961 0.3289 0.299
\({d}_{s}\) 1.94 1.58 1.00 1.00 1.0507 1.0644
\({g}_{1}\) 115.5584 130.3326 188.2936 187.1010 0 − 0.0000
\({g}_{2}\) − 187.6149 − 184.4716 − 177.0964 − 177.2108 − 0.0195 − 0.0195
\({g}_{3}\) − 53,639.0414 − 65,729.5709 − 89,846.4004 -89,247.7831 − 1.1584 − 1.0325
\({g}_{4}\) 400.4587 497.6636 691.2212 687.8356 − 0.0091 − 0.0105
\({g}_{5}\) − 9.9195 − 9.9733 − 9.9156 − 9.91635 − 0.001 − 0.0010
\({g}_{6}\) 133.9725 50.0452 49.7859 49.4697 − 0.0001 -0.0002
\({g}_{7}\) − 196.3651 − 197.7465 − 198.2822 − 198.2045 -0.0199 -0.0199
\({g}_{8}\) − 17,282.8387 − 10,585.6043 − 7076.4803 − 7760.8662 − 0.7011 − 0.6552
\({g}_{9}\) − 131.5924 − 241.1098 − 227.9268 − 214.1411 − 0.0306 − 0.0311
Cost \(\mathrm{\$}/piece\) 2.42 3.07 2.23 2.22 2.59 2.59
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