Defining constraints in Jenetics
I have previously worked with the MOEA Framework, which knows the concept of constraints. That is, a solution to a problem might have a good fitness, but is infeasible. For instance, when working with the knapsack problem, a particular combination of items may lead to a high profit, but their weight exceeds the knapsack's capacity. A corresponding fitness function would include lines like:
// Set the fitness (=> profit) of the solution (=> knapsack).
solution.setObjective(0, profit)
// Set the constrain (=> 0.0 if OK, , otherwise the distance to the boundary).
solution.setConstraint(0, (weight <= capacity) ? 0.0 : weight - capacity)
Another example in case of a multi-objective knapsack problem would be the constraint that a knapsack is not allowed to use items which are already used in another knapsack.
Has Jenetics something similar? Or how could I encode constraints as part of the fitness function (or somewhere else)?
java optimization genetic-algorithm
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I have previously worked with the MOEA Framework, which knows the concept of constraints. That is, a solution to a problem might have a good fitness, but is infeasible. For instance, when working with the knapsack problem, a particular combination of items may lead to a high profit, but their weight exceeds the knapsack's capacity. A corresponding fitness function would include lines like:
// Set the fitness (=> profit) of the solution (=> knapsack).
solution.setObjective(0, profit)
// Set the constrain (=> 0.0 if OK, , otherwise the distance to the boundary).
solution.setConstraint(0, (weight <= capacity) ? 0.0 : weight - capacity)
Another example in case of a multi-objective knapsack problem would be the constraint that a knapsack is not allowed to use items which are already used in another knapsack.
Has Jenetics something similar? Or how could I encode constraints as part of the fitness function (or somewhere else)?
java optimization genetic-algorithm
add a comment |
I have previously worked with the MOEA Framework, which knows the concept of constraints. That is, a solution to a problem might have a good fitness, but is infeasible. For instance, when working with the knapsack problem, a particular combination of items may lead to a high profit, but their weight exceeds the knapsack's capacity. A corresponding fitness function would include lines like:
// Set the fitness (=> profit) of the solution (=> knapsack).
solution.setObjective(0, profit)
// Set the constrain (=> 0.0 if OK, , otherwise the distance to the boundary).
solution.setConstraint(0, (weight <= capacity) ? 0.0 : weight - capacity)
Another example in case of a multi-objective knapsack problem would be the constraint that a knapsack is not allowed to use items which are already used in another knapsack.
Has Jenetics something similar? Or how could I encode constraints as part of the fitness function (or somewhere else)?
java optimization genetic-algorithm
I have previously worked with the MOEA Framework, which knows the concept of constraints. That is, a solution to a problem might have a good fitness, but is infeasible. For instance, when working with the knapsack problem, a particular combination of items may lead to a high profit, but their weight exceeds the knapsack's capacity. A corresponding fitness function would include lines like:
// Set the fitness (=> profit) of the solution (=> knapsack).
solution.setObjective(0, profit)
// Set the constrain (=> 0.0 if OK, , otherwise the distance to the boundary).
solution.setConstraint(0, (weight <= capacity) ? 0.0 : weight - capacity)
Another example in case of a multi-objective knapsack problem would be the constraint that a knapsack is not allowed to use items which are already used in another knapsack.
Has Jenetics something similar? Or how could I encode constraints as part of the fitness function (or somewhere else)?
java optimization genetic-algorithm
java optimization genetic-algorithm
edited Nov 21 '18 at 16:42
beatngu13
asked Nov 21 '18 at 12:50


beatngu13beatngu13
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Jenetics doesn't support constraints directly. You can set a phenotypeValidator
in the Engine.Builder
. This will reject Phenotypes
and recreate invalid individuals. Not exactly a constraint, but a kind of. The second possibility is to return the minimum fitness value for all objectives for such values.
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1 Answer
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active
oldest
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Jenetics doesn't support constraints directly. You can set a phenotypeValidator
in the Engine.Builder
. This will reject Phenotypes
and recreate invalid individuals. Not exactly a constraint, but a kind of. The second possibility is to return the minimum fitness value for all objectives for such values.
add a comment |
Jenetics doesn't support constraints directly. You can set a phenotypeValidator
in the Engine.Builder
. This will reject Phenotypes
and recreate invalid individuals. Not exactly a constraint, but a kind of. The second possibility is to return the minimum fitness value for all objectives for such values.
add a comment |
Jenetics doesn't support constraints directly. You can set a phenotypeValidator
in the Engine.Builder
. This will reject Phenotypes
and recreate invalid individuals. Not exactly a constraint, but a kind of. The second possibility is to return the minimum fitness value for all objectives for such values.
Jenetics doesn't support constraints directly. You can set a phenotypeValidator
in the Engine.Builder
. This will reject Phenotypes
and recreate invalid individuals. Not exactly a constraint, but a kind of. The second possibility is to return the minimum fitness value for all objectives for such values.
answered Nov 21 '18 at 15:33


Franz WilhelmstötterFranz Wilhelmstötter
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