Undergrad How to write main and sub objective for optimisation

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The discussion focuses on the challenge of formulating a main objective and a sub-objective in optimization problems, specifically minimizing two functions, X and Y. The goal is to minimize X first, then select the best solution for Y from the optimal solutions of X. The participants suggest that expressing this as a two-pass algorithm can clarify the approach, using mathematical notation to define feasible solutions and subsets. They also mention that in certain cases, minimizing Y can be incorporated as a constraint within the minimization of X. The conversation highlights the complexities of multi-criteria optimization and the need for specific problem details to determine feasible solutions.
Dominik Tugend
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I have had this problem that I didn't know how to write it properly in this thread.

Let's say I have two objective functions:
  1. minimize X
  2. minimize Y
Let's say I want 1. as main objective and 2. a sub objective - by that I mean if there is a set of optimal solutions for 1., then final solution can only be from that set and in such a way that it's the best for 2 from all of that set for 1.

My problem is I don't know how to write this down properly.

The only idea I have had so far doesn't work in all cases:
If 0 \leq Y \leq C and C \in \mathbb{R}_{\geq 0}, then I could rewrite the objective as
minimize X*(C+1) +Y
 
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Dominik Tugend said:
I have had this problem that I didn't know how to write it properly in this thread.

Let's say I have two objective functions:
  1. minimize X
  2. minimize Y
Let's say I want 1. as main objective and 2. a sub objective - by that I mean if there is a set of optimal solutions for 1., then final solution can only be from that set and in such a way that it's the best for 2 from all of that set for 1.

My problem is I don't know how to write this down properly.

The only idea I have had so far doesn't work in all cases:
If 0 \leq Y \leq C and C \in \mathbb{R}_{\geq 0}, then I could rewrite the objective as
minimize X*(C+1) +Y

You made the correct conclusion from the link on stackexchange. (As to the details on stackexchange - those posters know more about the question that I do.) However, if your are dealing with a problem in physics, your "preference relation" might be much simpler than such a thing is in theoretical economics. The preference relations in economics try to express human whims. (e.g. "I'd rather have 2 houses, 6 cars, 1 dog and 1 cat rather than have 3 houses, 4 cars, no dogs, and 1 cat".)

The most general way of writing the objective is to write it in a way that would translate into a "two pass" algorithm. You did that in words. You could make your statement look fancier by using more mathematical notation.

Let ##F## be the set of feasible solutions for the problem. Let ##S_x## be the set of solutions that minimize ##X(s)##, i.e. Let ##m_X = min\{ X(s): s \in F\}## and ##S_X = \{s: X(s) = m\}##. Then let ##S## be the subset of ##S_x## that minimizes ##Y(s)##, i.e. Let ##m_Y = min\{Y(s):s \in S_X\}## and ##S = \{s:Y(s)=m_Y\}##.

In special situations, you can attain the goal "2. minimize ##Y(s)##" by expressing it (or some property related to it) as a constraint on the problem "1. minimize ##X(s)##".

The relevant terminology for doing an internet search on the general question is "multi-criteria optimization" and "lexicographic multi-criteria optimization".

Your specific goal seems to be to express the problem as a problem of minimizing a single function ##F(s)##. How to do that (and whether it is possible) depends on the specific details of problem.

(Looking on the bright side, most of mathematics consists of finding interesting situations where things that are not always possible in general become possible.)
 
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Likes Dominik Tugend
Thank you very much for your reply :-)
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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