Fig 1.
Transformation of coordinates system.
Fig 2.
DE flowchart.
Fig 3.
Average path and computational cost at the 1000th generation with variation between differential weight and crossover at various population sizes of 10, 30, 50, 70, and 100 “Table A in S1 Dataset.”
Fig 4.
Estimation of optimum differential weight at NP = 10, G = 1000, and CR = 100%.
Fig 5.
Average path and computational cost obtained with crossover rates on the optimum differential weight over population sizes at various generations of 200, 400, 600, 800, and 1000 “Table B in S1 Dataset.”
Fig 6.
Optimum crossover and differential weight for various population sizes and generations “Table C in S1 Dataset.”
Fig 7.
Average path and computational cost between various population sizes and generation numbers at the optimum crossover and differential weight “Table D in S1 Dataset.”
Fig 8.
Optimum population size along generation number.
Fig 9.
Optimum differential weight and crossover along generation number.
Table 1.
Optimized setting of population size, differential weight & crossover at various maximum generation number.
Fig 10.
Average path cost changes in % when compared to the optimized parameter setting at maximum generation number of 1000 “Table E in S1 Dataset.”
Fig 11.
Average computational cost changes in % when compared to the optimized parameter setting at maximum generation number of 1000 “Table F in S1 Dataset.”