What is the best way to find the optimal solution of a non convex non linear optimization problem that really constitutes finding the optimal/ best combination of one member each from a number of groups or sub populations.
Each group of sub population has a number of members that are sequences - an array of elements.
The optimal solution is given by best matching a sequence or (as) member from each group or sub population.
It is similar to recombination of evolutionary algorithms (but not entirely identical to evolutionary algorithms).
Dear Brian,
probably due to my poor English I don't understand:
do you search an optimization problem or a way to solve it?
Maciej Karczyński , i want to solve a particular kind of optimization problem
manufacturing preparation and ordering are separated
balancing, is done in the preparation phase e.g. but linear programming
@Brian Barnard
Excuse me, but where is an attachment example.docx?
@Alexandru Szel
Dear Alexandru,
it seems that you want to introduce me your problem. I'm not an expert, although the topic of my work was an issue that I solved with genetic algorithm. Maybe I will can suggest you somewhat. But I can't get to your attachment. To verify, I added my attachment. It's OK. Maybe you did something wrong?
Yours Sincerely
Maciej Karczyński
an example with 2 objective functions is exemple.docx generalized to several functions
and more restrictions also read the text from examples.docx
It seems your example is similar to set covering. Genetic algorithm would be an ideal way to handle your issue.
Thanks all
I am thinking of a lookup type strategy to reference and expand the sub groups, to combine them
To me, the best optimal solutions to such problems are use:
1) Convectional neural works.
2) Multivariate exponential families of distributions.
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