# Questions tagged [multi-objective-optimization]

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.

66 questions
Filter by
Sorted by
Tagged with
58 views

### What are some important real life examples of multi objective optimization problem with box constraints to work on?

In the search of some of the important cutting edge many objective optimization problems to be solved using non-dominated sorting genetic algorithm (NSGA) and its variants.
105 views

### Is there a name for this variation of the generalized assignment problem?

All the input variables are positive float (x > 0). We have $M$ agents with limited amount of time $t_1,\dots,t_M$, $N$ tasks $task_1,\dots,task_N$ associated with duration $d_1,\dots, d_N$. Cost ...
1 vote
131 views

### Solving a Global Optimization problem using Differential Evolutionary Algorithm using R

I need to determine the global optimum results of this objective function. I define the problem by minimizing the squared difference as represented in function $f(q_1,q_2,\alpha_1,\alpha_2)$ The ...
1 vote
30 views

### Which Python package is suitable for finding the optimal non dominated set in multiobjective optimization?

I would like to know how to use pyhon or Cplex or both for finding the whole optimal pareto front for a biobjective mixed integer linear programming problem? Thanks
86 views

### Do you have to normalize objectives when using the weighted sum approch?

Do you have to normalize objectives when using the weighted sum approch when having multiple objectives? Actually I thought that I should do it. But now I have run several experiments with different ...
92 views

### Question about implementation method for optimization problem

Suppose we wanted to solve the following optimization problem: $$\inf_{x \geq 0}\sup_{y \in [0, 1];\ z > 0} f(x, y, z),$$ where $f(x, y, z)$ is some objective function with a closed form that can ...
493 views

### Determining the optimize lambda in Multi-Objective Optimization

I have a convex optimization problem: Maximize obj1 Minimize obj2 Some constraint Now to solve this problem, I used lambda to make it one problem: ...
1 vote
46 views

### Leontief utility function

For the Leontief utility function $$u_L(\lambda,y)=\min\{\lambda_1(r_1-y_1),\ldots,\lambda_m(r_m-y_m)\}$$ I would like to graphically show that, for $m=2$ and $\lambda\in\Lambda$ (for positive ...
1 vote
77 views

1 vote
1k views

### How define variable in CPLEX and What is diffrence between decision variables and variable in CPLEX

I want to code a problem by CPLEX, in this problem I have variables and decision variables, how define them? In this picture you can see the variables: which we have: I use these codes for variables:...
60 views

### What is a good approach to deciding which jobs (from a list of HPC jobs) should be ran locally vs. on the cloud given time & cost constraints?

Cloud computing has transformed the landscape of compute operations. Of course, there are still many labs/businesses with local, large-scale compute clusters. For those businesses who keep the ...
271 views

### Multi-objective function normalization

I am trying to solve the multi-objective function of my linear program. Are there another approaches other than the weighted sum approximation?
Consider an optimization problem with $n>3$ objectives. For handling this there exists often two approaches: a) some weighting of the objectives, b) fix an order of objectives and then optimize ...