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Learn about routing heterogeneous electric vehicle fleets in this research seminar that explores a complex optimization problem incorporating multiple charging modes and time-dependent waiting functions at charging stations. Discover a path-based mixed-integer linear programming formulation and a two-component algorithmic framework for solving the Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions (HEVRP-NL). Examine how the first component uses iterated local search to generate optimal solutions and create high-quality route pools, while the second component employs a set-partitioning model for route combination. Study the benchmark instances developed specifically for HEVRP-NL and understand how the proposed model achieves optimal solutions for small-scale instances and outperforms existing approaches for large-scale scenarios through extensive computational testing.
