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adapt the code to split up predictions form the inbounds

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This commit is contained in:
Sven Czarnian
2021-11-13 22:55:04 +01:00
parent eba9e2deab
commit 8b34f622a3
9 changed files with 280 additions and 267 deletions
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46
aman/sys/aco/Ant.py
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@@ -9,26 +9,27 @@ import itertools
from aman.sys.aco.Configuration import Configuration
from aman.sys.aco.RunwayManager import RunwayManager
from aman.types.Inbound import Inbound
from aman.sys.aco.Node import Node
# This class implements a single ant of the following paper:
# https://sci-hub.mksa.top/10.1109/cec.2019.8790135
class Ant:
def __init__(self, pheromoneTable : np.array, configuration : Configuration):
def __init__(self, pheromoneTable : np.array, configuration : Configuration, nodes):
self.Configuration = configuration
self.Nodes = nodes
self.RunwayManager = RunwayManager(self.Configuration)
self.InboundSelected = [ False ] * len(self.Configuration.Inbounds)
self.InboundScore = np.zeros([ len(self.Configuration.Inbounds), 1 ])
self.InboundSelected = [ False ] * len(self.Nodes)
self.InboundScore = np.zeros([ len(self.Nodes), 1 ])
self.PheromoneMatrix = pheromoneTable
self.SequenceDelay = timedelta(seconds = 0)
self.Sequence = None
def qualifyDelay(delay, inbound, runway):
def qualifyDelay(delay, node, runway):
if 0.0 > delay.total_seconds():
delay = timedelta(seconds = 0)
# calculate the heuristic scaling to punish increased delays for single inbounds
scaledDelay = delay.total_seconds() / inbound.ArrivalCandidates[runway.Name].MaximumTimeToLose.total_seconds()
scaledDelay = delay.total_seconds() / node.ArrivalCandidates[runway.Name].MaximumTimeToLose.total_seconds()
return max(1.0 / (99.0 * (scaledDelay ** 2) + 1), 0.01)
# Implements function (5), but adapted to the following logic:
@@ -37,8 +38,8 @@ class Ant:
# - Calculates a ratio between the inbound delay and the unused runway time
# - Weight the overall ratio based on maximum time to lose to punish high time to lose rates while other flights are gaining time
def heuristicInformation(self, preceeding : int, current : int):
rwy, eta, unusedRunwayTime = self.RunwayManager.selectArrivalRunway(self.Configuration.Inbounds[current], True, self.Configuration.EarliestArrivalTime)
inboundDelay = eta - self.Configuration.Inbounds[current].ArrivalCandidates[rwy.Name].InitialArrivalTime
rwy, eta, unusedRunwayTime = self.RunwayManager.selectArrivalRunway(self.Nodes[current], True, self.Configuration.EarliestArrivalTime)
inboundDelay = eta - self.Nodes[current].ArrivalCandidates[rwy.Name].InitialArrivalTime
if 0.0 > inboundDelay.total_seconds():
inboundDelay = timedelta(seconds = 0)
@@ -49,7 +50,7 @@ class Ant:
fraction /= 60.0
# calculate the heuristic scaling to punish increased delays for single inbounds
weight = Ant.qualifyDelay(inboundDelay, self.Configuration.Inbounds[current], rwy)
weight = Ant.qualifyDelay(inboundDelay, self.Nodes[current], rwy)
return weight * self.PheromoneMatrix[preceeding, current] * ((1.0 / (fraction or 1)) ** self.Configuration.Beta)
@@ -86,18 +87,19 @@ class Ant:
return None
def associateInbound(self, inbound : Inbound, earliestArrivalTime : datetime):
def associateInbound(self, node : Node, earliestArrivalTime : datetime):
# prepare the statistics
rwy, eta, _ = self.RunwayManager.selectArrivalRunway(inbound, True, self.Configuration.EarliestArrivalTime)
rwy, eta, _ = self.RunwayManager.selectArrivalRunway(node, True, self.Configuration.EarliestArrivalTime)
eta = max(earliestArrivalTime, eta)
inbound.PlannedRunway = rwy
inbound.PlannedStar = inbound.ArrivalCandidates[rwy.Name].Star
inbound.PlannedArrivalTime = eta
inbound.InitialArrivalTime = inbound.ArrivalCandidates[rwy.Name].InitialArrivalTime
self.RunwayManager.RunwayInbounds[rwy.Name] = inbound
node.Inbound.PlannedRunway = rwy
node.Inbound.PlannedStar = node.ArrivalCandidates[rwy.Name].Star
node.Inbound.PlannedArrivalTime = eta
node.Inbound.PlannedArrivalRoute = node.ArrivalCandidates[rwy.Name].ArrivalRoute
node.Inbound.InitialArrivalTime = node.ArrivalCandidates[rwy.Name].InitialArrivalTime
self.RunwayManager.RunwayInbounds[rwy.Name] = node
delay = inbound.PlannedArrivalTime - inbound.InitialArrivalTime
delay = node.Inbound.PlannedArrivalTime - node.Inbound.InitialArrivalTime
if 0.0 < delay.total_seconds():
return delay, rwy
else:
@@ -108,8 +110,8 @@ class Ant:
# select the first inbound
self.InboundSelected[first] = True
delay, rwy = self.associateInbound(self.Configuration.Inbounds[first], self.Configuration.EarliestArrivalTime)
self.InboundScore[0] = Ant.qualifyDelay(delay, self.Configuration.Inbounds[first], rwy)
delay, rwy = self.associateInbound(self.Nodes[first], self.Configuration.EarliestArrivalTime)
self.InboundScore[0] = Ant.qualifyDelay(delay, self.Nodes[first], rwy)
self.Sequence.append(first)
self.SequenceDelay += delay
@@ -119,9 +121,9 @@ class Ant:
break
self.InboundSelected[index] = True
delay, rwy = self.associateInbound(self.Configuration.Inbounds[index], self.Configuration.EarliestArrivalTime)
delay, rwy = self.associateInbound(self.Nodes[index], self.Configuration.EarliestArrivalTime)
self.SequenceDelay += delay
self.InboundScore[len(self.Sequence)] = Ant.qualifyDelay(delay, self.Configuration.Inbounds[index], rwy)
self.InboundScore[len(self.Sequence)] = Ant.qualifyDelay(delay, self.Nodes[index], rwy)
self.Sequence.append(index)
# update the local pheromone
@@ -130,7 +132,7 @@ class Ant:
self.PheromoneMatrix[self.Sequence[-2], self.Sequence[-1]] = max(self.Configuration.ThetaZero, update)
# validate that nothing went wrong
if len(self.Sequence) != len(self.Configuration.Inbounds):
if len(self.Sequence) != len(self.Nodes):
self.SequenceDelay = None
self.SequenceScore = None
self.Sequence = None