Files
Sportstime/SportsTime/Planning/Engine/GameDAGRouter.swift
Trey t f5e509a9ae Add region-based filtering and route length diversity
- Add RegionMapSelector UI for geographic trip filtering (East/Central/West)
- Add RouteFilters module for allowRepeatCities preference
- Improve GameDAGRouter to preserve route length diversity
  - Routes now grouped by city count before scoring
  - Ensures 2-city trips appear alongside longer trips
  - Increased beam width and max options for better coverage
- Add TripOptionsView filters (max cities slider, pace filter)
- Remove TravelStyle section from trip creation (replaced by region selector)
- Clean up debug logging from DataProvider and ScenarioAPlanner

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-09 15:18:37 -06:00

525 lines
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Swift
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//
// GameDAGRouter.swift
// SportsTime
//
// Time-expanded DAG + Beam Search algorithm for route finding.
//
// Key insight: This is NOT "which subset of N games should I attend?"
// This IS: "what time-respecting paths exist through a graph of games?"
//
// The algorithm:
// 1. Bucket games by calendar day
// 2. Build directed edges where time moves forward AND driving is feasible
// 3. Beam search: keep top K paths at each depth
// 4. Dominance pruning: discard inferior paths
//
// Complexity: O(days × beamWidth × avgNeighbors) 900 operations for 5-day, 78-game scenario
// (vs 2^78 for naive subset enumeration)
//
import Foundation
import CoreLocation
enum GameDAGRouter {
// MARK: - Configuration
/// Default beam width - how many partial routes to keep at each step
/// Increased to ensure we preserve diverse route lengths (short and long trips)
private static let defaultBeamWidth = 50
/// Maximum options to return (increased to provide more diverse trip lengths)
private static let maxOptions = 50
/// Buffer time after game ends before we can depart (hours)
private static let gameEndBufferHours: Double = 3.0
/// Maximum days ahead to consider for next game (1 = next day only, 5 = allows multi-day drives)
private static let maxDayLookahead = 5
// MARK: - Public API
/// Finds best routes through the game graph using DAG + beam search.
///
/// This replaces the exponential GeographicRouteExplorer with a polynomial-time algorithm.
///
/// - Parameters:
/// - games: All games to consider, in any order (will be sorted internally)
/// - stadiums: Dictionary mapping stadium IDs to Stadium objects
/// - constraints: Driving constraints (number of drivers, max hours per day)
/// - anchorGameIds: Games that MUST appear in every valid route (for Scenario B)
/// - allowRepeatCities: If false, each city can only appear once in a route
/// - beamWidth: How many partial routes to keep at each depth (default 30)
///
/// - Returns: Array of valid game combinations, sorted by score (most games, least driving)
///
static func findRoutes(
games: [Game],
stadiums: [UUID: Stadium],
constraints: DrivingConstraints,
anchorGameIds: Set<UUID> = [],
allowRepeatCities: Bool = true,
beamWidth: Int = defaultBeamWidth
) -> [[Game]] {
// Edge cases
guard !games.isEmpty else { return [] }
if games.count == 1 {
// Single game - just return it if it satisfies anchors
if anchorGameIds.isEmpty || anchorGameIds.contains(games[0].id) {
return [games]
}
return []
}
if games.count == 2 {
// Two games - check if both are reachable
let sorted = games.sorted { $0.startTime < $1.startTime }
if canTransition(from: sorted[0], to: sorted[1], stadiums: stadiums, constraints: constraints) {
if anchorGameIds.isSubset(of: Set(sorted.map { $0.id })) {
return [sorted]
}
}
// Can't connect them - return individual games if they satisfy anchors
if anchorGameIds.isEmpty {
return [[sorted[0]], [sorted[1]]]
}
return []
}
// Step 1: Sort games chronologically
let sortedGames = games.sorted { $0.startTime < $1.startTime }
// Step 2: Bucket games by calendar day
let buckets = bucketByDay(games: sortedGames)
let sortedDays = buckets.keys.sorted()
guard !sortedDays.isEmpty else { return [] }
// Step 3: Initialize beam with first day's games
var beam: [[Game]] = []
if let firstDayGames = buckets[sortedDays[0]] {
for game in firstDayGames {
beam.append([game])
}
}
// Also include option to skip first day entirely and start later
// (handled by having multiple starting points in beam)
for dayIndex in sortedDays.dropFirst().prefix(maxDayLookahead - 1) {
if let dayGames = buckets[dayIndex] {
for game in dayGames {
beam.append([game])
}
}
}
// Step 4: Expand beam day by day
for (_, dayIndex) in sortedDays.dropFirst().enumerated() {
let todaysGames = buckets[dayIndex] ?? []
var nextBeam: [[Game]] = []
for path in beam {
guard let lastGame = path.last else { continue }
let lastGameDay = dayIndexFor(lastGame.startTime, referenceDate: sortedGames[0].startTime)
// Only consider games on this day or within lookahead
if dayIndex > lastGameDay + maxDayLookahead {
// This path is too far behind, keep it as-is
nextBeam.append(path)
continue
}
// Try adding each of today's games
for candidate in todaysGames {
// Check for repeat city violation during route building
if !allowRepeatCities {
let candidateCity = stadiums[candidate.stadiumId]?.city ?? ""
let pathCities = Set(path.compactMap { stadiums[$0.stadiumId]?.city })
if pathCities.contains(candidateCity) {
continue // Skip - would violate allowRepeatCities
}
}
if canTransition(from: lastGame, to: candidate, stadiums: stadiums, constraints: constraints) {
let newPath = path + [candidate]
nextBeam.append(newPath)
}
}
// Also keep the path without adding a game today (allows off-days)
nextBeam.append(path)
}
// Dominance pruning + beam truncation
beam = pruneAndTruncate(nextBeam, beamWidth: beamWidth, stadiums: stadiums)
}
// Step 5: Filter routes that contain all anchors
let routesWithAnchors = beam.filter { path in
let pathGameIds = Set(path.map { $0.id })
return anchorGameIds.isSubset(of: pathGameIds)
}
// Step 6: Ensure geographic diversity in results
// Group routes by their primary region (city with most games)
// Then pick the best route from each region
let finalRoutes = selectDiverseRoutes(routesWithAnchors, stadiums: stadiums, maxCount: maxOptions)
print("🔍 DAG: Input games=\(games.count), beam final=\(beam.count), withAnchors=\(routesWithAnchors.count), final=\(finalRoutes.count)")
if let best = finalRoutes.first {
print("🔍 DAG: Best route has \(best.count) games")
}
return finalRoutes
}
/// Compatibility wrapper that matches GeographicRouteExplorer's interface.
/// This allows drop-in replacement in ScenarioAPlanner and ScenarioBPlanner.
static func findAllSensibleRoutes(
from games: [Game],
stadiums: [UUID: Stadium],
anchorGameIds: Set<UUID> = [],
allowRepeatCities: Bool = true,
stopBuilder: ([Game], [UUID: Stadium]) -> [ItineraryStop]
) -> [[Game]] {
// Use default driving constraints
let constraints = DrivingConstraints.default
return findRoutes(
games: games,
stadiums: stadiums,
constraints: constraints,
anchorGameIds: anchorGameIds,
allowRepeatCities: allowRepeatCities
)
}
// MARK: - Day Bucketing
/// Groups games by calendar day index (0 = first day of trip, 1 = second day, etc.)
private static func bucketByDay(games: [Game]) -> [Int: [Game]] {
guard let firstGame = games.first else { return [:] }
let referenceDate = firstGame.startTime
var buckets: [Int: [Game]] = [:]
for game in games {
let dayIndex = dayIndexFor(game.startTime, referenceDate: referenceDate)
buckets[dayIndex, default: []].append(game)
}
return buckets
}
/// Calculates the day index for a date relative to a reference date.
private static func dayIndexFor(_ date: Date, referenceDate: Date) -> Int {
let calendar = Calendar.current
let refDay = calendar.startOfDay(for: referenceDate)
let dateDay = calendar.startOfDay(for: date)
let components = calendar.dateComponents([.day], from: refDay, to: dateDay)
return components.day ?? 0
}
// MARK: - Transition Feasibility
/// Determines if we can travel from game A to game B.
///
/// Requirements:
/// 1. B starts after A (time moves forward)
/// 2. We have enough days between games to complete the drive
/// 3. We can arrive at B before B starts
///
private static func canTransition(
from: Game,
to: Game,
stadiums: [UUID: Stadium],
constraints: DrivingConstraints
) -> Bool {
// Time must move forward
guard to.startTime > from.startTime else {
return false
}
// Same stadium = always feasible (no driving needed)
if from.stadiumId == to.stadiumId { return true }
// Get stadiums
guard let fromStadium = stadiums[from.stadiumId],
let toStadium = stadiums[to.stadiumId] else {
// Missing stadium info - can't calculate distance, reject to be safe
print("⚠️ DAG: Stadium lookup failed - from:\(stadiums[from.stadiumId] != nil) to:\(stadiums[to.stadiumId] != nil)")
return false
}
let fromCoord = fromStadium.coordinate
let toCoord = toStadium.coordinate
// Calculate driving time
let distanceMiles = TravelEstimator.haversineDistanceMiles(
from: CLLocationCoordinate2D(latitude: fromCoord.latitude, longitude: fromCoord.longitude),
to: CLLocationCoordinate2D(latitude: toCoord.latitude, longitude: toCoord.longitude)
) * 1.3 // Road routing factor
let drivingHours = distanceMiles / 60.0 // Average 60 mph
// Calculate available driving time between games
// After game A ends (+ buffer), how much time until game B starts (- buffer)?
let departureTime = from.startTime.addingTimeInterval(gameEndBufferHours * 3600)
let deadline = to.startTime.addingTimeInterval(-3600) // 1 hour buffer before game
let availableSeconds = deadline.timeIntervalSince(departureTime)
let availableHours = availableSeconds / 3600.0
// Calculate how many driving days we have
// Each day can have maxDailyDrivingHours of driving
let calendar = Calendar.current
let fromDay = calendar.startOfDay(for: from.startTime)
let toDay = calendar.startOfDay(for: to.startTime)
let daysBetween = calendar.dateComponents([.day], from: fromDay, to: toDay).day ?? 0
// Available driving hours = days between * max per day
// (If games are same day, daysBetween = 0, but we might still have hours available)
let maxDrivingHoursAvailable: Double
if daysBetween == 0 {
// Same day - only have hours between games
maxDrivingHoursAvailable = max(0, availableHours)
} else {
// Multi-day - can drive each day
maxDrivingHoursAvailable = Double(daysBetween) * constraints.maxDailyDrivingHours
}
// Check if we have enough driving time
guard drivingHours <= maxDrivingHoursAvailable else {
return false
}
// Also verify we can arrive before game starts (sanity check)
guard availableHours >= drivingHours else {
return false
}
return true
}
// MARK: - Geographic Diversity
/// Selects diverse routes from the candidate set.
/// Ensures diversity by BOTH route length (city count) AND primary city.
/// This guarantees users see 2-city trips alongside 5+ city trips.
private static func selectDiverseRoutes(
_ routes: [[Game]],
stadiums: [UUID: Stadium],
maxCount: Int
) -> [[Game]] {
guard !routes.isEmpty else { return [] }
// Group routes by city count (route length)
var routesByLength: [Int: [[Game]]] = [:]
for route in routes {
let cityCount = Set(route.compactMap { stadiums[$0.stadiumId]?.city }).count
routesByLength[cityCount, default: []].append(route)
}
// Sort routes within each length by score
for (length, lengthRoutes) in routesByLength {
routesByLength[length] = lengthRoutes.sorted {
scorePath($0, stadiums: stadiums) > scorePath($1, stadiums: stadiums)
}
}
// Allocate slots to each length category
// Goal: ensure at least 1 route per length category if available
let sortedLengths = routesByLength.keys.sorted()
let minPerLength = max(1, maxCount / max(1, sortedLengths.count))
var selectedRoutes: [[Game]] = []
var selectedIds = Set<String>()
// First pass: take best route(s) from each length category
for length in sortedLengths {
if selectedRoutes.count >= maxCount { break }
if let lengthRoutes = routesByLength[length] {
let toTake = min(minPerLength, lengthRoutes.count, maxCount - selectedRoutes.count)
for route in lengthRoutes.prefix(toTake) {
let key = route.map { $0.id.uuidString }.joined(separator: "-")
if !selectedIds.contains(key) {
selectedRoutes.append(route)
selectedIds.insert(key)
}
}
}
}
// Second pass: fill remaining slots, prioritizing geographic diversity
if selectedRoutes.count < maxCount {
// Group remaining routes by primary city
var remainingByCity: [String: [[Game]]] = [:]
for route in routes {
let key = route.map { $0.id.uuidString }.joined(separator: "-")
if !selectedIds.contains(key) {
let city = getPrimaryCity(for: route, stadiums: stadiums)
remainingByCity[city, default: []].append(route)
}
}
// Sort by score within each city
for (city, cityRoutes) in remainingByCity {
remainingByCity[city] = cityRoutes.sorted {
scorePath($0, stadiums: stadiums) > scorePath($1, stadiums: stadiums)
}
}
// Round-robin from each city
let sortedCities = remainingByCity.keys.sorted { city1, city2 in
let score1 = remainingByCity[city1]?.first.map { scorePath($0, stadiums: stadiums) } ?? 0
let score2 = remainingByCity[city2]?.first.map { scorePath($0, stadiums: stadiums) } ?? 0
return score1 > score2
}
var cityIndices: [String: Int] = [:]
while selectedRoutes.count < maxCount {
var addedAny = false
for city in sortedCities {
if selectedRoutes.count >= maxCount { break }
let idx = cityIndices[city] ?? 0
if let cityRoutes = remainingByCity[city], idx < cityRoutes.count {
let route = cityRoutes[idx]
let key = route.map { $0.id.uuidString }.joined(separator: "-")
if !selectedIds.contains(key) {
selectedRoutes.append(route)
selectedIds.insert(key)
addedAny = true
}
cityIndices[city] = idx + 1
}
}
if !addedAny { break }
}
}
return selectedRoutes
}
/// Gets the primary city for a route (where most games are played).
private static func getPrimaryCity(for route: [Game], stadiums: [UUID: Stadium]) -> String {
var cityCounts: [String: Int] = [:]
for game in route {
let city = stadiums[game.stadiumId]?.city ?? "Unknown"
cityCounts[city, default: 0] += 1
}
return cityCounts.max(by: { $0.value < $1.value })?.key ?? "Unknown"
}
// MARK: - Scoring and Pruning
/// Scores a path. Higher = better.
/// Prefers: more games, less driving, geographic coherence
private static func scorePath(_ path: [Game], stadiums: [UUID: Stadium]) -> Double {
// Handle empty or single-game paths
guard path.count > 1 else {
return Double(path.count) * 100.0
}
let gameCount = Double(path.count)
// Calculate total driving
var totalDriving: Double = 0
for i in 0..<(path.count - 1) {
totalDriving += estimateDrivingHours(from: path[i], to: path[i + 1], stadiums: stadiums)
}
// Score: heavily weight game count, penalize driving
return gameCount * 100.0 - totalDriving * 2.0
}
/// Estimates driving hours between two games.
private static func estimateDrivingHours(
from: Game,
to: Game,
stadiums: [UUID: Stadium]
) -> Double {
// Same stadium = 0 driving
if from.stadiumId == to.stadiumId { return 0 }
guard let fromStadium = stadiums[from.stadiumId],
let toStadium = stadiums[to.stadiumId] else {
return 5.0 // Fallback: assume 5 hours
}
let fromCoord = fromStadium.coordinate
let toCoord = toStadium.coordinate
let distanceMiles = TravelEstimator.haversineDistanceMiles(
from: CLLocationCoordinate2D(latitude: fromCoord.latitude, longitude: fromCoord.longitude),
to: CLLocationCoordinate2D(latitude: toCoord.latitude, longitude: toCoord.longitude)
) * 1.3
return distanceMiles / 60.0
}
/// Prunes dominated paths and truncates to beam width.
/// Maintains diversity by both ending city AND route length to ensure short trips aren't eliminated.
private static func pruneAndTruncate(
_ paths: [[Game]],
beamWidth: Int,
stadiums: [UUID: Stadium]
) -> [[Game]] {
// Remove exact duplicates
var uniquePaths: [[Game]] = []
var seen = Set<String>()
for path in paths {
let key = path.map { $0.id.uuidString }.joined(separator: "-")
if !seen.contains(key) {
seen.insert(key)
uniquePaths.append(path)
}
}
// Group paths by unique city count (route length)
// This ensures we keep short trips (2 cities) alongside long trips (5+ cities)
var pathsByLength: [Int: [[Game]]] = [:]
for path in uniquePaths {
let cityCount = Set(path.compactMap { stadiums[$0.stadiumId]?.city }).count
pathsByLength[cityCount, default: []].append(path)
}
// Sort paths within each length group by score
for (length, lengthPaths) in pathsByLength {
pathsByLength[length] = lengthPaths.sorted {
scorePath($0, stadiums: stadiums) > scorePath($1, stadiums: stadiums)
}
}
// Allocate beam slots proportionally to length groups, with minimum per group
let sortedLengths = pathsByLength.keys.sorted()
let minPerLength = max(2, beamWidth / max(1, sortedLengths.count))
var pruned: [[Game]] = []
// First pass: take minimum from each length group
for length in sortedLengths {
if let lengthPaths = pathsByLength[length] {
let toTake = min(minPerLength, lengthPaths.count)
pruned.append(contentsOf: lengthPaths.prefix(toTake))
}
}
// Second pass: fill remaining slots with best paths overall
if pruned.count < beamWidth {
let remaining = beamWidth - pruned.count
let prunedIds = Set(pruned.map { $0.map { $0.id.uuidString }.joined(separator: "-") })
// Get all paths not yet added, sorted by score
var additional = uniquePaths.filter {
!prunedIds.contains($0.map { $0.id.uuidString }.joined(separator: "-"))
}
additional.sort { scorePath($0, stadiums: stadiums) > scorePath($1, stadiums: stadiums) }
pruned.append(contentsOf: additional.prefix(remaining))
}
// Final truncation
return Array(pruned.prefix(beamWidth))
}
}