Application of Genetic Algorithms for Driverless Subway Train Energy Optimization

Table 1

Energy saving achievable with different optimization methods [26].

Optimization methods	Energy saving with; EED as compared to; nonoptimized driving
Nonlinear programming	Up to 25%
Fuzzy logic	From 25% to 30%
Genetic algorithm	From 30% to 40%