Develops the first approximation algorithms with guarantees for line planning using heterogeneous fleets and multiple resource constraints, achieving 1-1/e ratio for cost-free case via randomized rounding.
Maximizing non-monotone submodular set functions subject to different constraints: Combined algorithms
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Approximation Algorithms for Line Planning with Heterogeneous Fleets and Multiple Resource Constraints
Develops the first approximation algorithms with guarantees for line planning using heterogeneous fleets and multiple resource constraints, achieving 1-1/e ratio for cost-free case via randomized rounding.