1. How
to change the initialize population (in
algorithms)
2. How
to encode in int[] (solution type)
3. How
to make it evaluate fitness function (in
problem, evaluate, set objective value for a solution(gene))
4. What
is the use of evaluateConstraints (in problem,
evaluate, set #constraintsViolated for a solution(gene))
5. How
to sort the population (there is a sort function
in algorithm.execute())
6. How
to change the evaluation of crossover and mutation (is it working on clone)? (Yes)
7. What
I should do about for quality indicator
8. The objective functions in the problem are to be minimized (the smaller the better).
Main(Problem,
Algorithm, Operator, parameters)
Problem
(the problem to be solve, #obj,#constraint,#var) ->SolutionType(Types that
is used by the genes) -> CreateVariables(Create contents in the genes for
initial population)
Algorithm (e.g., GA, execute()) -> create initial population (SolutionSet(Population) ->
Solution (Gene Instance))
For IBEA
Spread, etc. are just quality indicators that it is used to judged the multiobjective optimization, it is not used in the process. The indicator used in the process is the hypervolume indicator.
