java.lang.Object
- libai.ants.algorithms.Metaheuristic

All Implemented Interfaces:

java.util.Comparator<Ant>

Direct Known Subclasses:

AntColonySystem, AntSystem, MMAS
```
public abstract class Metaheuristic
extends java.lang.Object
implements java.util.Comparator<Ant>
```
This is the core class of the Ant Framework. It defines the basic operations that any ACO algorithm must implement. This is an abstract class that must be extended by the class that implements a particular ACO algorithm for instance: AntSystem, AntColonySystem, MIX-MAX ACO, ...
This class is composed of an instance of the Enviroment class, which holds the necesary information to solve a given optimization problem

Field Summary

Fields
Modifier and Type	Field	Description
`protected static int`	`alpha`	Determine the relevance of the pheromone trail tau_ij when an Ant decides the next node to be incorporated in a solution.
`protected Ant[]`	`Ants`	Enviroment's ant array local copy
`protected java.util.List<java.lang.Integer>`	`bestSolution`	Vector that holds the global best solution found
`protected static int`	`beta`	Determine the relevance of the heuristic information n_ij when an Ant decides the next node to be incorporated in a solution.
`protected java.util.HashMap<java.lang.Integer,java.util.List<Node>>`	`candidates`	Vector that holds the candidate list
`protected int`	`currentIterationNumber`	current iteration number
`protected static int`	`destinationNode`	destination node of the search
`protected Enviroment`	`E`	Instance of an Enviroment which holds all of the necesary information to solve an optimizacion problem
`protected Graph`	`Graph`	Enviroment's graph local copy
`protected static int`	`initialNode`	initial node of the search
`protected static int`	`maxNumIterations`	the maximum number of iterations
`protected int`	`numberOfAnts`	Enviroment's number of ants local copy
`protected int`	`numberOfNodes`	Enviroment's graph number of node
`protected java.util.HashMap<java.lang.Integer,java.lang.Double>`	`Parameters`	Hashtable that holds the parameters
`protected Matrix`	`Pheromones`	Enviroment's pheromones matrix local copy

Constructor Summary

Constructors
Modifier Constructor Description

protected Metaheuristic()
Constructor.

protected Metaheuristic(Enviroment E)
Constructor.

Method Summary

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method	Description
`abstract void`	`candidateList(int max)`	Generate, per node in the graph, a list of candidates nodes according to some problem specific heuristic.
`abstract void`	`checkParameters()`	Checks whether or not all of the algorithm's parameters exists.
`int`	`compare(Ant o1, Ant o2)`	Compares to ants' solutions based on the quality metric of f.
`abstract java.util.List<java.lang.Integer>`	`constrains(int i, java.util.List<java.lang.Integer> currentSolution)`	Given a node in the graph and an ant's current solution, returns a list of possible nodes to visit.
`abstract void`	`daemonActions()`	This function is called on each iteration and it provides a way to implement centralized actions
`abstract int`	`decisionRule(int i, java.util.List<java.lang.Integer> currentSolution)`	Used by ants to decided the next node to visit.
`double`	`f(java.util.List<java.lang.Integer> solution)`	This function determines the lenght of a solution
`java.util.List<java.lang.Integer>`	`getBestSolution()`	Returns best solution
`int`	`getCurrentIterationNumber()`	Returns current iteration number
`Enviroment`	`getE()`	Returns the enviroment
`int`	`getNumberOfNodes()`	Gets the number of nodes of the problem graph
`double`	`getParam(int key)`
`abstract double`	`heuristicInfo(double number)`	Calculates the heuristic information.
`abstract void`	`pheromonesEvaporation()`	Evaporates the pheromone trail contained in the enviroment E according to some ACO algorithm specific logic
`abstract void`	`pheromonesUpdate()`	Updates the pheromone trail contained in the enviroment E according to some ACO algorithm specific logic
`protected void`	`setE(Enviroment E)`	Sets the enviroment
`void`	`setNumberOfNodes(int numberOfNodes)`	Sets the number of nodes of the graph problem
`protected void`	`setParam(int key, double param)`	Sets a parameter
`abstract void`	`solve()`	This is the body of the algorithm.

Methods inherited from interface java.util.Comparator
equals, reversed, thenComparing, thenComparing, thenComparing, thenComparingDouble, thenComparingInt, thenComparingLong

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - initialNode
```
protected static final int initialNode
```
    initial node of the search
    
    See Also:
    
    Constant Field Values
  - destinationNode
```
protected static final int destinationNode
```
    destination node of the search
    
    See Also:
    
    Constant Field Values
  - maxNumIterations
```
protected static final int maxNumIterations
```
    the maximum number of iterations
    
    See Also:
    
    Constant Field Values
  - alpha
```
protected static final int alpha
```
    Determine the relevance of the pheromone trail tau_ij when an Ant decides the next node to be incorporated in a solution. Used in the decisionRule() method
    
    See Also:
    
    Constant Field Values
  - beta
```
protected static final int beta
```
    Determine the relevance of the heuristic information n_ij when an Ant decides the next node to be incorporated in a solution. Used in the decisionRule() method
    
    See Also:
    
    Constant Field Values
  - E
```
protected Enviroment E
```
    Instance of an Enviroment which holds all of the necesary information to solve an optimizacion problem
  - Parameters
```
protected java.util.HashMap<java.lang.Integer,java.lang.Double> Parameters
```
    Hashtable that holds the parameters
  - bestSolution
```
protected java.util.List<java.lang.Integer> bestSolution
```
    Vector that holds the global best solution found
  - candidates
```
protected java.util.HashMap<java.lang.Integer,java.util.List<Node>> candidates
```
    Vector that holds the candidate list
  - currentIterationNumber
```
protected int currentIterationNumber
```
    current iteration number
  - Pheromones
```
protected Matrix Pheromones
```
    Enviroment's pheromones matrix local copy
  - numberOfAnts
```
protected int numberOfAnts
```
    Enviroment's number of ants local copy
  - Ants
```
protected Ant[] Ants
```
    Enviroment's ant array local copy
  - Graph
```
protected Graph Graph
```
    Enviroment's graph local copy
  - numberOfNodes
```
protected int numberOfNodes
```
    Enviroment's graph number of node
- Constructor Detail
  - Metaheuristic
```
protected Metaheuristic(Enviroment E)
```
    Constructor. Allocates the enviroment.
    
    Parameters:
    
    E - enviroment
  - Metaheuristic
```
protected Metaheuristic()
```
    Constructor. Empty constructor.
- Method Detail
  - getE
```
public Enviroment getE()
```
    Returns the enviroment
    
    Returns:
    
    the enviroment.
  - setE
```
protected void setE(Enviroment E)
```
    Sets the enviroment
    
    Parameters:
    
    E - the enviroment.
  - getNumberOfNodes
```
public int getNumberOfNodes()
```
    Gets the number of nodes of the problem graph
    
    Returns:
    
    number of nodes of the problem graph
  - setNumberOfNodes
```
public void setNumberOfNodes(int numberOfNodes)
```
    Sets the number of nodes of the graph problem
    
    Parameters:
    
    numberOfNodes - numberOfNodes
  - setParam
```
protected void setParam(int key,
                        double param)
```
    Sets a parameter
    
    Parameters:
    
    key - of the parameter
    
    param - the value of the parameter
  - getParam
```
public double getParam(int key)
```
  - pheromonesUpdate
```
public abstract void pheromonesUpdate()
```
    Updates the pheromone trail contained in the enviroment E according to some ACO algorithm specific logic
  - pheromonesEvaporation
```
public abstract void pheromonesEvaporation()
```
    Evaporates the pheromone trail contained in the enviroment E according to some ACO algorithm specific logic
  - decisionRule
```
public abstract int decisionRule(int i,
                                 java.util.List<java.lang.Integer> currentSolution)
```
    Used by ants to decided the next node to visit.
    
    Parameters:
    
    i - source node
    
    currentSolution - currentSolution
    
    Returns:
    
    destination node
  - solve
```
public abstract void solve()
                    throws AntFrameworkException
```
    This is the body of the algorithm. Implements the fundamental logic and calls to other functions: pheromonesUpdate,pheromonesEvaporation.. according to some ACO algorithm specific logic
    
    Throws:
    
    AntFrameworkException - AntFrameworkException
  - checkParameters
```
public abstract void checkParameters()
                              throws java.lang.Exception
```
    Checks whether or not all of the algorithm's parameters exists. If some obligatory parameter do not exist, the function throws an exception. If some other parameter do not exists but it is possible to set a default value, here is the place to do it.
    
    Throws:
    
    java.lang.Exception - Exception
  - candidateList
```
public abstract void candidateList(int max)
```
    Generate, per node in the graph, a list of candidates nodes according to some problem specific heuristic. The candidates are stored in this class's candidates hashtable
    
    Parameters:
    
    max - maximum number of candidates allowed
  - constrains
```
public abstract java.util.List<java.lang.Integer> constrains(int i,
                                                             java.util.List<java.lang.Integer> currentSolution)
```
    Given a node in the graph and an ant's current solution, returns a list of possible nodes to visit. This function must be implemented on the problem level, and usually obeys some problem related restricctions For instance, in the case of the TSP, this function must check which nodes have been visited and return only those wich have not been visited. For the case of the short route, this function returns all adjacents nodes to node i.
    
    Parameters:
    
    i - current node
    
    currentSolution - ant's current solutin
    
    Returns:
    
    list of possible nodes to visit
  - daemonActions
```
public abstract void daemonActions()
```
    This function is called on each iteration and it provides a way to implement centralized actions
  - heuristicInfo
```
public abstract double heuristicInfo(double number)
```
    Calculates the heuristic information. Must be implement on the problem level
    
    Parameters:
    
    number - a number being considered
    
    Returns:
    
    heuristic information
  - getBestSolution
```
public java.util.List<java.lang.Integer> getBestSolution()
```
    Returns best solution
    
    Returns:
    
    best solution
  - getCurrentIterationNumber
```
public int getCurrentIterationNumber()
```
    Returns current iteration number
    
    Returns:
    
    current iteration number
  - f
```
public double f(java.util.List<java.lang.Integer> solution)
```
    This function determines the lenght of a solution
    
    Parameters:
    
    solution - a path constructed by an ant
    
    Returns:
    
    lenght of a path
  - compare
```
public int compare(Ant o1,
                   Ant o2)
```
    Compares to ants' solutions based on the quality metric of f.
    
    Specified by:
    
    compare in interface java.util.Comparator<Ant>
    
    Parameters:
    
    o1 - ant 1
    
    o2 - ant 2
    
    Returns:
    
    0 if solution of ant_1 = solution of ant_2, 1 if solution of ant_1 greater than solution of ant_2 and -1 otherwise

Modifier	Constructor	Description
`protected`	`Metaheuristic()`	Constructor.
`protected`	`Metaheuristic(Enviroment E)`	Constructor.

Class Metaheuristic

Field Summary

Constructor Summary

Method Summary

Methods inherited from interface java.util.Comparator

Methods inherited from class java.lang.Object

Field Detail

initialNode

destinationNode

maxNumIterations

alpha

beta

E

Parameters

bestSolution

candidates

currentIterationNumber

Pheromones

numberOfAnts

Ants

Graph

numberOfNodes

Constructor Detail

Metaheuristic

Metaheuristic

Method Detail

getE

setE

getNumberOfNodes

setNumberOfNodes

setParam

getParam

pheromonesUpdate

pheromonesEvaporation

decisionRule

solve

checkParameters

candidateList

constrains

daemonActions

heuristicInfo

getBestSolution

getCurrentIterationNumber

f

compare