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Results tagged with multi-objective-optimization
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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.
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How to compute Generational Distance, Inverted Generational Distance, Epsilon Indicator, and...
In order to find the quality indicators like Generational Distance, Inverted Generational Distance, Epsilon Indicator, and HyperVolume for a Pareto front I want to normalize the values of approximatio …
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Which multi-objective optimization algorithm should one select?
The multi-objective optimization problem in my case is defined below:
Objective 1: Minimize $f_1(X_1,X_2)=C_1X_1+C_2X_2+C_3X_1^2+C_4X_2^2+C_5X_1^2X_2^2$
Objective 2: Minimize $f_2(X_1,X_2)=D_1X_1+D_ …
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Relationship between Hypervolume and population size, number of generations, and number of f...
I have a multi-objective optimization with the following properties:
Objective function: two non-linear functions and one linear function
Decision variable: two real variables (Bounded)
Constraint: th …
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Metaheuristics or Exact algorithms to solve a non-linear multi-objective optimization problem?
The multi-objective optimization problem settings are as defined below:
Objective 1: Minimize $f_1(X_1,X_2)=C_0+C_1(1/X_1)+C_2(X_2/X_1)$
Objective 2: Minimize $f_2(X_1,X_2)=D_0+D_1X_1+D_2X_2+D_3(X_2 …
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How to linearize a non-convex optimization objective function?
The non-convex multi-objective optimization problem in my case is defined below:
Objective 1: Minimize $f_1(X_1,X_2)=C_0+C_1(1/X_1)+C_2(X_2/X_1)+C_3X_1+C_4X_2+C_5(X_2^2/X_1)$
Objective 2: Minimize $ …
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What methods are used to solve multi-objective optimization problem with non-linear objectiv...
Case 1: NLP
When either the objective function or at least one of the constraints or both are non-linear it is a NLP. We use generalized reduced gradient or Quadratic Programming to solve NLP. However …
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Branch and bound method for solving non-convex integer non-linear multi-objective optimizati...
Following are the characteristics of my problem:
Objective function: two non-linear functions and one linear function
Decision variable: two integer variables ($X_1$ and $X_2$)
Constraint: three (two …
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