A NSGA-II algorithm with permutation-partition encoding optimizes bike rebalancing routes under demand uncertainty for three objectives, producing well-distributed trade-off solutions that outperform greedy baselines on Barcelona's 460-station Bicing system.
Comparison of multiobjective evolutionary algorithms for prioritized urban waste collection in Montevideo, Uruguay.Electronic Notes in Discrete Mathematics, 69:93–100
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Robust Multi-Objective Optimization for Bicycle Rebalancing in Shared Mobility Systems
A NSGA-II algorithm with permutation-partition encoding optimizes bike rebalancing routes under demand uncertainty for three objectives, producing well-distributed trade-off solutions that outperform greedy baselines on Barcelona's 460-station Bicing system.