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Results tagged with multi-objective-optimization
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user 4777
Multi-objective optimization is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Involve two or more optimization goals that are conflicting, meaning that improvement to one objective comes at the expense of another objective. The two methods for perform a multi-objetive-optimization are Pareto and scalarization.
3
votes
Accepted
Branch and bound method for solving non-convex integer non-linear multi-objective optimizati...
Yes we can. Branch and bound can both deal the integer variables and with the potenial non convexities of the non-linear functions. Most branch and bound methods can also handle constraints. Depending …
- 4,049
3
votes
Accepted
How to linearize a non-convex optimization objective function?
One traditional method to linearize multi-linear/polynomial constraints are McCormick envelopes, which are refined over time. Here is a great resource on those. A single objective solver that uses th …
- 4,049
2
votes
Does a pre-calculated lower bound of an MILP problem help?
There are different approaches to solve MILP problems since you didn't mention what kind of solver you are using i assume you mean in context of branch and bound solver.
Feasible solutions are found u …
- 4,049
1
vote
Accepted
How to compute Generational Distance, Inverted Generational Distance, Epsilon Indicator, and...
The reference front is another name for the pareto front of the problem. You find it either by solving the problem symbolically, constructing a problem around some pareto front or running and global o …
- 4,049