The objective of this problem is to generate a travel path between two or more cities while considering various factors such as cost, time and ease of transit (the number of hops).
The objective of this problem is to generate a travel path between two or more cities while considering various factors such as cost, time and ease of transit (the number of hops). The general idea is as follows: The path from a City – SOURCE to a City – DESTINATION is calculated through an adaption of Dijkstra’s algorithm. The adaption integrates various factors that are of importance to travelers and generates an optimal route corresponding to a traveler’s priorities. The program functions as follows. Users can make use of commands to add a City, add a Flight path between two cities and add a Train path between two cities. Subsequently they can plan a trip between two cities, utilizing the information that was previously entered. The relative cost of travel is used to determine the shortest path from SOURCE to DESTINATION. The relative cost of travel can be termed as the weight of each edge (path) between two vertices (Cities).
The approach used to implement Dijkstra’s algorithm primarily utilizes
- Priority Queue - To sort Cities by ascending order of relative cost of travel
- HashMaps - To store relative costs for each City, to store the departure city for each destination and to store the number of hops from SOURCE to DESTINATION
- ArrayLists - To store Cities, Flights & Trains
- HashSet – To store Vertices that’ve been visited (in Dijkstra’s algorithm)
City.java This class represents Cities: Each object of type City is associated with the following attributes: Variables: cityName - City name testRequired - States if a test is Required for Unvaccinated individuals to the city timeToTest - Time to Take a test nightlyHotelCost - Hotel Cost for 1 night cost_from_source - Cost to Travel from source to this City
Flight.java This class represents Flights between cities. Each object of type Flight is associated with the following attributes: Variables: startCity - Start city destinationCity - Destination city flightTime - Time to travel flightCost - Cost of travel
Train.java This class represents Trains between cities. Each object of type Train is associated with the following attributes: Variables: startCity - Start city destinationCity - Destination city flightTime - Time to travel flightCost - Cost of travel
Hop.java This class represents a path/edge between two cities. Each object of type Hop is associated with the following attributes: Variables: start - Start city destination - Destination city relative_cost - Relative cost of visiting city from the source time - Time to travel cost - Cost of travel mode - Mode of travel (Fly / Train)
Graph.java This class represents a path/edge between two cities. Each object of type Hop is associated with the following attributes: Variables: Vertices – A HashSet which stores all vertices (Cities) adjVertices – A HashMap which stores a set of Cities that are connected to each City. This serves as the adjacency list.
TravelAssistant.java This class represents a path/edge between two cities. Each object of type Hop is associated with the following attributes: Variables: Cities – Stores a unique list of Cities Hops - Stores a unique list of Travel Paths between Cities Flights – Stores a unique list Flight paths between Cities Trains – Stores a unique list Train paths between Cities
Methods: encode(): This method accepts an input file from the standard input, parses the contents of the file, encodes it and stores the output in another text file. Parameters: String input_filename - Path to the file which’s to be encoded int level – The maximum number of characters which can be parsed in the last cycle is determined by 2^level. boolean reset – If reset is true, frequency counts are reset at the beginning of every cycle. String output_filename - The path of the file, in which the output is stored.