 All Implemented Interfaces:
OptimizationProblem<BitVector>
,Problem<BitVector>
This class implements Ackley's Mix problem, an artificial landscape that
is a mix of the OneMax, TwoMax, Trap, and Plateau problems, which provides
for a landscape that combines all of the properties of these benchmarking
problems. For details of the 5 component search landscapes, see the
OneMaxAckley
, TwoMax
, Trap
, Porcupine
,
and Plateaus
classes.
The Mix problem is defined as the following maximization problem. Maximize the fitness function, f(x), of bit string x, such that we do the following. Break x into 5 equalsized segments, and sum the fitnesses of the 5 segments, where the first segment is scores as a OneMax instance, the second segment is scored as a TwoMax instance, the third segment is scored as a Trap instance, the fourth segment is scores as a Porcupine instance, and the fifth is scored as one segment of a Plateau instance. Note that the fifth segment is not scored directly as a full Plateau instance, but rather if all of the bits of that segment are 1s, then it scores as 10*p, where p is the length of that segment, and otherwise it scores as 0. The optimum occurs when the entire bit string is all 1s, which has a maximum fitness of 10*n.
The value
method implements the original maximization
version of the Mix problem, as described above. The algorithms
of the ChipsnSalsa library are defined for minimization, requiring
a cost function. The cost
method implements the equivalent
as the following minimization problem: minimize
cost(x) = 10*n  f(x), where f(x) is the Mix function as defined above.
The global optima
is all 1bits, which has a cost equal to 0.
The Mix problem
was introduced by David Ackley in the following paper:
David H. Ackley. An empirical study of bit vector function optimization. Genetic
Algorithms and Simulated Annealing,
pages 170204, 1987.

Constructor Summary

Method Summary
Modifier and TypeMethodDescriptiondouble
Computes the cost of a candidate solution to the problem instance.boolean
isMinCost
(double cost) Checks if a given cost value is equal to the minimum theoretical cost across all possible solutions to the problem instance, where lower cost implies better solution.double
minCost()
A lower bound on the minimum theoretical cost across all possible solutions to the problem instance, where lower cost implies better solution.double
Computes the value of the candidate solution within the usual constraints and interpretation of the problem.Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.cicirello.search.problems.OptimizationProblem
costAsDouble, getSolutionCostPair

Constructor Details

Mix
public Mix()Constructs an instance of Ackley's Mix problem.


Method Details

cost
Description copied from interface:OptimizationProblem
Computes the cost of a candidate solution to the problem instance. The lower the cost, the more optimal the candidate solution. Specified by:
cost
in interfaceOptimizationProblem<BitVector>
 Parameters:
candidate
 The candidate solution to evaluate. Returns:
 The cost of the candidate solution. Lower cost means better solution.

minCost
public double minCost()Description copied from interface:OptimizationProblem
A lower bound on the minimum theoretical cost across all possible solutions to the problem instance, where lower cost implies better solution. The default implementation returns Double.NEGATIVE_INFINITY. Specified by:
minCost
in interfaceOptimizationProblem<BitVector>
 Returns:
 A lower bound on the minimum theoretical cost of the problem instance.

value
Description copied from interface:OptimizationProblem
Computes the value of the candidate solution within the usual constraints and interpretation of the problem. Specified by:
value
in interfaceOptimizationProblem<BitVector>
 Parameters:
candidate
 The candidate solution to evaluate. Returns:
 The actual optimization value of the candidate solution.

isMinCost
public boolean isMinCost(double cost) Description copied from interface:OptimizationProblem
Checks if a given cost value is equal to the minimum theoretical cost across all possible solutions to the problem instance, where lower cost implies better solution. Specified by:
isMinCost
in interfaceOptimizationProblem<BitVector>
 Parameters:
cost
 The cost to check. Returns:
 true if cost is equal to the minimum theoretical cost,
