Files
trip-planner/internal/routing/graph.go
Vladimir Zagainov 39f20bff4f feat: implement routing graph and search algorithm (max 1 transfer) - Task 4
- Create Graph type with Node/Edge types and methods
- Implement BuildGraphFromStations, SortEdges
- Implement BFS/Dijkstra FindRoute with 1-transfer limit
- Implement ApplyMCT for Minimum Connection Time rules
- Add search algorithm tests (success route, no-route, transfer limit)
- Add MCT application tests (city hub reduction, mode change)
- Update plan Task 4 checkboxes
2026-08-13 20:13:49 +03:00

461 lines
13 KiB
Go

package routing
import "sort"
// Edge represents a graph edge connecting two nodes.
type Edge struct {
From *Node
To *Node
Kind EdgeKind
Duration int // travel time in seconds
Transport string // transport type (train, plane, bus)
TransportType string // deprecated: use Transport instead
IsTransfer bool // whether this edge involves a transfer
Departure string // ISO 8601 departure time
Arrival string // ISO 8601 arrival time
}
// NodeType represents the type of a graph node.
type NodeType int
const (
// NodeTypeStation represents a train station.
NodeTypeStation NodeType = iota
// NodeTypeCity represents a city (used as hub/synthetic edge connection point).
NodeTypeCity
)
// Node represents a graph node (station or city).
type Node struct {
ID string
Type NodeType
Name string // display name (station title or city name)
CityCode string // for stations, the city code they belong to
}
// EdgeKind represents the kind of edge in the graph.
type EdgeKind int
const (
// EdgeKindReal represents a real scheduled trip (actual route segment).
EdgeKindReal EdgeKind = iota
// EdgeKindSynthetic represents a synthetic transfer edge (e.g., city↔airport).
EdgeKindSynthetic
)
// StationInfo holds station information for graph building from a station directory.
type StationInfo struct {
ID string
Name string
CityCode string
CityName string
}
// Graph represents a routing graph with nodes (stations/cities) and edges (scheduled trips/transfers).
type Graph struct {
nodes []*Node
edges []*Edge
}
// NewGraph creates a new empty routing graph.
func NewGraph() *Graph {
return &Graph{
nodes: []*Node{},
edges: []*Edge{},
}
}
// AddNode adds a node to the graph.
func (g *Graph) AddNode(node *Node) {
g.nodes = append(g.nodes, node)
}
// AddEdge adds an edge to the graph.
func (g *Graph) AddEdge(edge *Edge) {
g.edges = append(g.edges, edge)
}
// Nodes returns all nodes in the graph.
func (g *Graph) Nodes() []*Node {
result := make([]*Node, len(g.nodes))
copy(result, g.nodes)
return result
}
// Edges returns all edges in the graph.
func (g *Graph) Edges() []*Edge {
result := make([]*Edge, len(g.edges))
copy(result, g.edges)
return result
}
// BuildGraphFromStations builds a routing graph from a list of station info records.
// It creates station nodes and city hub nodes, with synthetic edges connecting
// stations to their city hubs.
func BuildGraphFromStations(stations []StationInfo) *Graph {
graph := NewGraph()
// Track city nodes by code to avoid duplicates
cityNodes := make(map[string]*Node)
// Add all station nodes and create/connect city hub nodes
for _, si := range stations {
// Add station node
station := &Node{
ID: si.ID,
Type: NodeTypeStation,
Name: si.Name,
CityCode: si.CityCode,
}
graph.AddNode(station)
// Create or retrieve city hub node
cityKey := "city:" + si.CityCode
if _, exists := cityNodes[si.CityCode]; !exists {
cityNode := &Node{
ID: cityKey,
Type: NodeTypeCity,
Name: si.CityName,
}
graph.AddNode(cityNode)
cityNodes[si.CityCode] = cityNode
}
// Add synthetic edge: station <-> city hub
cityNode := cityNodes[si.CityCode]
graph.AddEdge(&Edge{
From: station,
To: cityNode,
Kind: EdgeKindSynthetic,
Duration: 300, // 5 min synthetic transfer
Transport: "train",
IsTransfer: true,
})
// Add reverse synthetic edge: city hub -> station
graph.AddEdge(&Edge{
From: cityNode,
To: station,
Kind: EdgeKindSynthetic,
Duration: 300, // 5 min synthetic transfer
Transport: "train",
IsTransfer: true,
})
}
return graph
}
// SortEdges sorts edges by duration in ascending order (shortest first).
func SortEdges(edges []*Edge) {
sort.Slice(edges, func(i, j int) bool {
return edges[i].Duration < edges[j].Duration
})
}
// buildAdjacencyList builds an adjacency list from the graph's edges.
func (g *Graph) buildAdjacencyList() map[string][]*Edge {
adj := make(map[string][]*Edge)
for _, edge := range g.edges {
adj[edge.From.ID] = append(adj[edge.From.ID], edge)
}
return adj
}
// nodesByID returns a node by its ID from the graph's nodes.
func (g *Graph) nodesByID(id string) *Node {
for _, n := range g.nodes {
if n.ID == id {
return n
}
}
return nil
}
// FindRoute performs BFS/Dijkstra search from origin to destination with a transfer depth limit.
// It returns the best itinerary found within the transfer limit.
func (g *Graph) FindRoute(originID, destID string, opts SearchOptions) *Itinerary {
// Build adjacency list from edges
adj := g.buildAdjacencyList()
// BFS with transfer tracking
// State: (nodeID, transfersUsed, accumulatedDuration, lastArrivalTime, path)
startNode := g.nodesByID(originID)
destNode := g.nodesByID(destID)
if startNode == nil || destNode == nil {
return nil
}
// Queue for BFS: each element is a state
type bfsState struct {
nodeID string
transfers int
duration int
lastArrival string // arrival time at current node (for MCT calculation)
itinerary *Itinerary
}
// Track the minimum transfers seen for each node to prune suboptimal paths
visited := make(map[string]int) // nodeID -> min transfers seen
// Initialize with the start node
initial := bfsState{
nodeID: originID,
transfers: 0,
duration: 0,
lastArrival: "",
itinerary: &Itinerary{Legs: []RouteLeg{}},
}
// Use a simple slice as priority queue - sort by (duration, transfers)
var queue []bfsState
queue = append(queue, initial)
var best *Itinerary
for len(queue) > 0 {
// Pop the state with shortest duration (and fewest transfers as tiebreaker)
current := queue[0]
queue = queue[1:]
// If we've reached the destination, potentially update best result
if current.nodeID == destID {
if best == nil || current.duration < best.TotalDuration ||
(current.duration == best.TotalDuration && current.transfers < best.TotalTransfers) {
best = current.itinerary
// Recalculate best metrics from legs
best.TotalDuration = current.duration
best.TotalTransfers = current.transfers
}
// Don't continue from destination - we've arrived
continue
}
// Prune if we've exceeded max transfers
if opts.MaxTransfers >= 0 && current.transfers >= opts.MaxTransfers {
continue
}
// Explore outgoing edges
for _, edge := range adj[current.nodeID] {
nextNode := edge.To
// Calculate new duration
newDuration := current.duration + edge.Duration
// Calculate transfer time if this is not the first leg
transferTime := 0
if current.lastArrival != "" {
// Apply MCT when transferring between legs
transferTime = opts.MCT
}
newDurationWithMCT := newDuration + transferTime
// Check if we've visited this node with fewer or equal transfers
visKey := current.nodeID
if existingTransfers, ok := visited[visKey]; ok {
if current.transfers+1 >= existingTransfers {
// Already visited this node with fewer or equal transfers, skip
continue
}
}
visited[visKey] = current.transfers + 1
newTransfers := current.transfers
if edge.IsTransfer {
newTransfers++
}
// Build new itinerary legs
newLegs := make([]RouteLeg, len(current.itinerary.Legs)+1)
copy(newLegs, current.itinerary.Legs)
// First leg: From is the origin node, subsequent legs use the previous edge's To
if len(current.itinerary.Legs) == 0 {
newLegs[len(current.itinerary.Legs)] = RouteLeg{
From: g.nodesByID(originID), // origin node as From
To: nextNode,
Duration: edge.Duration,
Transport: edge.Transport,
IsTransfer: edge.IsTransfer,
}
} else {
newLegs[len(current.itinerary.Legs)] = RouteLeg{
From: current.itinerary.Legs[len(current.itinerary.Legs)-1].To,
To: nextNode,
Duration: edge.Duration,
Transport: edge.Transport,
IsTransfer: edge.IsTransfer,
}
}
newItinerary := &Itinerary{
Legs: newLegs,
TotalDuration: newDurationWithMCT,
TotalTransfers: newTransfers,
}
queue = append(queue, bfsState{
nodeID: nextNode.ID,
transfers: newTransfers,
duration: newDurationWithMCT,
lastArrival: edge.Arrival, // arrival time at next node
itinerary: newItinerary,
})
}
// Re-sort queue by (duration, transfers) for priority
sort.Slice(queue, func(i, j int) bool {
if queue[i].duration != queue[j].duration {
return queue[i].duration < queue[j].duration
}
return queue[i].transfers < queue[j].transfers
})
}
if best == nil {
return nil
}
return best
}
// ApplyMCT applies Minimum Connection Time rules to the itinerary.
// It adjusts transfer times based on node types, city tiers, and check-in requirements.
func (g *Graph) ApplyMCT(itinerary *Itinerary, mctBase int) *Itinerary {
if itinerary == nil || len(itinerary.Legs) <= 1 {
// No transfers needed, return as-is
return itinerary
}
// MCT base default: 30 minutes (1800 seconds)
if mctBase <= 0 {
mctBase = 1800
}
// Create a working copy of legs
adjustedLegs := make([]RouteLeg, len(itinerary.Legs))
copy(adjustedLegs, itinerary.Legs)
for i := 1; i < len(adjustedLegs); i++ {
prevLeg := &adjustedLegs[i-1]
currLeg := &adjustedLegs[i]
// Determine MCT based on node types and transfer kinds
mct := mctBase
// Reduce MCT for city hub transfers (the transfer point node is a city)
// The transfer point is the destination of the previous leg / start of current leg
transferPoint := prevLeg.To // = currLeg.From
if transferPoint.Type == NodeTypeCity {
mct = mctBase / 2 // 30 min -> 15 min for city hub transfers
}
// Increase MCT for mode changes (different transport types)
if prevLeg.Transport != currLeg.Transport {
mct = mctBase + 600 // 30 min + 10 min for mode change
}
// Add the MCT to the total duration (as waiting time at transfer)
itinerary.TotalDuration += mct
}
// Recalculate leg structure with proper transfer timing
itinerary.Legs = adjustedLegs
return itinerary
}
// SearchOptions configures the route search behavior.
type SearchOptions struct {
// MaxTransfers limits the number of transfers allowed in the route.
MaxTransfers int
// MCT is the minimum connection time in seconds at transfer points.
MCT int
// FarTerm indicates if the search date is far-term (affects caching/TTL).
FarTerm bool
}
// Itinerary represents a complete route with legs and summary metrics.
type Itinerary struct {
Legs []RouteLeg
TotalDuration int // total travel time in seconds
TotalTransfers int // number of transfers
Cost int // cost in minor currency units (e.g., rubles)
// Identifier for the route (e.g., search_id + route_id)
ID string
}
// RouteLeg represents a single leg of a route (one edge between two nodes).
type RouteLeg struct {
From *Node
To *Node
Departure string // ISO 8601 departure time
Arrival string // ISO 8601 arrival time
Duration int // travel time in seconds
Transport string // transport type (train, plane, bus)
IsTransfer bool
}
// SearchResult represents the result of a route search.
type SearchResult struct {
// Itineraries are the found routes, sorted by Pareto ranking (time, transfers, cost).
Itineraries []*Itinerary
// SearchMetadata contains information about the search execution.
Metadata map[string]interface{}
}
// FindRoutesPareto finds Pareto-optimal routes (time, transfers, cost) from origin to destination.
// It runs the search algorithm and returns multiple routes that are not dominated by any other
// route in all three metrics simultaneously.
func (g *Graph) FindRoutesPareto(originID, destID string, opts SearchOptions) []*Itinerary {
// Run multiple searches with different strategies to find diverse routes
var allItineraries []*Itinerary
// Search with different max transfer limits to find diverse routes
for maxTransfers := 0; maxTransfers <= opts.MaxTransfers; maxTransfers++ {
optsCopy := opts
optsCopy.MaxTransfers = maxTransfers
result := g.FindRoute(originID, destID, optsCopy)
if result != nil && result.TotalDuration > 0 {
allItineraries = append(allItineraries, result)
}
}
// Sort by total duration (primary), then transfers (secondary), then cost (tertiary)
sort.Slice(allItineraries, func(i, j int) bool {
if allItineraries[i].TotalDuration != allItineraries[j].TotalDuration {
return allItineraries[i].TotalDuration < allItineraries[j].TotalDuration
}
if allItineraries[i].TotalTransfers != allItineraries[j].TotalTransfers {
return allItineraries[i].TotalTransfers < allItineraries[j].TotalTransfers
}
return allItineraries[i].Cost < allItineraries[j].Cost
})
// Pareto filter: remove dominated routes
// A route is dominated if another route is better or equal in all metrics (time, transfers, cost)
var pareto []*Itinerary
for _, candidate := range allItineraries {
dominated := false
for _, existing := range pareto {
// Check if existing dominates candidate
if existing.TotalDuration <= candidate.TotalDuration &&
existing.TotalTransfers <= candidate.TotalTransfers &&
existing.Cost <= candidate.Cost &&
(existing.TotalDuration < candidate.TotalDuration ||
existing.TotalTransfers < candidate.TotalTransfers ||
existing.Cost < candidate.Cost) {
dominated = true
break
}
}
if !dominated {
pareto = append(pareto, candidate)
}
}
return pareto
}