Open liaicheng opened 5 years ago
Hi @liaicheng,
the fitness reaches the minimum value for you 2 objectives: Vector(2.0, 2.0, 2.0). This is the ideal point of the Pareto front you're computing since you're 2 objectives range from 2.0 to 5.0 and MGO always minimize the fitness. What do you expect ?
Romain
@romainreuillon thanks for your replying. Yes, I got it. What i expect is minimize to zero. Anyway , I update my fitness, it can work better.
HI, that's my first experience to use multi objectives algorithm with your code. My fitness function as below:
and call function as below:
But the result can't be restrained. Something wrong?
here is the result:
Result(Vector(2.0, 2.0, 2.0),Vector(),Vector(100.47800000000001, 39.574, 195.672)) Result(Vector(2.0000000000000004, 2.0, 2.0),Vector(),Vector(78.646, 39.726, 162.348)) Result(Vector(2.0, 2.000000000000001, 2.0),Vector(),Vector(89.562, 39.650000000000006, 179.01)) Result(Vector(2.0, 2.0000000000000004, 2.0),Vector(),Vector(89.562, 39.650000000000006, 179.01)) Result(Vector(2.000000000000001, 2.0, 2.0),Vector(),Vector(78.646, 39.726, 162.348)) Result(Vector(2.0, 2.000000000000002, 2.0),Vector(),Vector(89.562, 39.650000000000006, 179.01)) Result(Vector(2.0, 2.0000000000000018, 2.0),Vector(),Vector(89.562, 39.650000000000006, 179.01)) Result(Vector(2.0, 2.0000000000000013, 2.0),Vector(),Vector(89.562, 39.650000000000006, 179.01))