I have a multi-objective optimization with the following properties:
Objective function: thee minimization objective functions) two non-linear functions and one linear function
Decision variable: two real variables (Bounded)
Constraint: three linear constraint (two bounding constraint and one relationship constraint)
Problem type: non-convex
Solution required: Global optimum
I have used two heuristic algorithms to solve the problem NSGA-II and NSGA-III.
I have performed NSGA-II and NSGA-III for the following instances (population size, number of generations, maximum number of functional evaluations(i.e. pop size x no. of gen)): (100,10,1000), (100,50,5000),(100,100,10000), (500, 10, 1000), (500, 50, 25000), and (500,100,50000).
My observations:
Hypervolume increases with increase in number of functional evaluations. However, for a given population size, as the number of generation increases the hypervolume reduces. Which I think should rather increase. Why am I getting such an answer?
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