Fig. 12 | Scientific Reports

Fig. 12

From: Energy-efficient scheduling of AGV-assisted robotic flexible flowshops under learning and processing time uncertainty

Fig. 12The alternative text for this image may have been generated using AI.

Pareto frontiers obtained by AUGMECON, NSGA-II, and NSGA for test problem PN1. The figure compares the nondominated solutions in terms of makespan and total energy consumption, illustrating how each algorithm explores the trade-off between the two objectives. AUGMECON provides a limited but accurate set of points, whereas NSGA-II shows better diversity and coverage of the search space compared to NSGA.

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