Initializes the routing engine with transit data.
-List of all transit trips.
-Graph of walking connections between stops.
-Minimum transfer times for each stop.
-Calculates optimal journeys for a specific departure time.
-The starting Stop ID.
-The destination Stop ID.
-The exact departure time.
-A list of optimal Journey objects.
-Finds the best journeys within a time window, filtering for Pareto optimality across all departures.
-The starting Stop ID.
-The destination Stop ID.
-The start of the departure window.
-The duration of the window to search (e.g. 3600s).
-A deduplicated list of the best journeys found in the time range.
-Executes the McRAPTOR algorithm to find all non-dominated paths to the destination.
-The starting Stop ID.
-The destination Stop ID.
-The time of departure.
-A Bag containing Pareto-optimal labels for the destination.
-Sets the penalty multiplier for walking (default is 1).
-The multiplier for walking duration cost.
-Pre-built route indices for McRAPTOR. Rebuilt when the transit graph trips change.
+Optionaloverlay: McRaptorQueryOverlayOptionaloverlay: McRaptorQueryOverlayOptionaloverlay: McRaptorQueryOverlayStaticbuildA container for Labels at a specific stop that maintains a Pareto frontier. Only keeps labels that are not dominated by any other label in the bag.
-Attempts to add a label to the bag.
True if the label was added (it was non-dominated), False otherwise.
-Checks if the bag is empty.
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Implementation of the McRAPTOR (Multi-Criteria Round-Based Public Transit Routing) algorithm. -Optimizes for arrival time, walking distance, and number of transfers.
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