Table 8 Decision vectors obtained by chosen algorithms for the TTDO problem.

From: Resistance–capacitance optimizer: a physics-inspired population-based algorithm for numerical and industrial engineering computation problems

Algorithm

\({x}_{1}\)

\({x}_{2}\)

Min

Mean

STD

RT

FRT

RCOA

0.7868

0.2880

186.386

186.386

2.542E−14

0.049479

1.500

GWO

0.7869

0.2878

186.386

186.386

1.422E−05

0.049479

3.000

SCA

0.7876

0.2862

186.387

186.396

1.164E−02

0.049479

6.167

JAYA

0.7868

0.2880

186.386

186.390

5.117E−03

0.021421

5.167

AOA

0.7868

0.2880

186.386

186.386

2.542E−14

0.057292

1.500

CrSA

0.7862

0.2893

186.386

186.387

8.731E−04

0.388021

4.667

MRFO

0.7885

0.2847

186.387

186.572

2.666E−01

11.59635

7.167

MPA

0.7865

0.2887

186.386

186.480

1.259E−01

1.1875

6.833

  1. Significant values are in bold.