In multi objective optimization, when I change the value of one constant in objective function I am getting pareto front for some xyz constants and for another set of constants, i am not getting any pareto front(pareto converges to point). So is this possible??
Dear Maruti Patil,
Please see question posed through ResearchGate by Vaiju Kalkhambkar in Jul 8, 2014 here folowing link:
-Can you help me in solving an objective function in optimization ...
https://www.researchgate.net/.../Can_you_help_me_in_solving_an...
Also i suggest for you a links and attached files in topics.
-Multiobjective Evolutionary Algorithms and Applications
https://books.google.dz/books?isbn=1846281326
-Multi-Objective Optimization Using Evolutionary Algorithms
https://books.google.dz/books?isbn=047187339X
-Evolutionary Multi-objective Optimization in Uncertain Environments: ...
https://books.google.dz/books?isbn=3540959769
Best regards
Read the following book may be help you
"Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications"
for Eckart Zitzler
Greeting Maruti,
It is definitely possible. For me this happened on a real-world problem, where for some inputs the solution was a single point on the Pareto. This happens when the objectives araren't independant.
Best Regards,
Miha
Dear Maruti,
Multi-objective optimization is recommended when you have conflicting objectives. Sometimes happens the objectives are correlated or there is an appropriated aggregation function that you can use, in those cases mono-objective optimization could be more appropriate
Dear Maruti,
Yes, it is possible.
Think of two simple objectives:
min c_1^T x and min c_2^T x
to be minimized on a polytope (a set satisfying linear constraints).
It is possible that c_1 and c_2 are sufficiently close to each other
and therefore both objectives attain their minima at the same vertex
of the polytope.
With best regards,
Jacek Gondzio
Y if one is monotonous function of the other, for instance. Or that plus a function that depends on an other sets of variables. A minus sign or ()^-1 plus anything else provides the other examples.
Is it possible to use the multi-objective algorithm to optimize the multiple non-conflicting objectives? The multiple objectives are dependent, it is not appropriate to transform the multiple objectives into the single objective. If the multi-objective algorithm cannot use for the non-conflicting objectives, how to optimize the multiple non-conflicting objectives?
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