Published online: 26 October 2013This paper presents a new approach to robustness analysis in multi-objective optimization problems aimed at obtaining the most robust Pareto front solutions and distributing the solutions along the most robust regions of the optimal Pareto set. A new set of test problems accounting for the different types of robustness cases is presented in this study. Non-dominated solutions are classified according to their degree of robustness and are distributed along the Pareto front according to specific algorithm parameter values. Verification of the proposed method is carried out using the developed test problems and artificial and real world benchmark test problems present in the literature.This work was partially s...
Robust optimization tries to find flexible solutions when solving problems with uncertain scenarios ...
Optimizing multiple conflicting objectives results in more than one optimal solution (known as Paret...
Robust multi-objective optimization has emerged as an active research. A recent study proposed two d...
Published online: 26 October 2013This paper presents a new approach to robustness analysis in multi-...
This paper presents a new approach to robustness analysis in multi-objective optimization problems a...
This work discusses robustness assessment during multi-objective optimization with a Multi-Objective...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
In real-world applications, it is often desired that a solution is not only of high performance, but...
Jin Y, Sendhoff B. Trade-Off between Performance and Robustness: An Evolutionary Multiobjective Appr...
In optimization studies including multi-objective optimization, the main focus is usually placed in ...
In order to evaluate the relative performance of optimization algorithms benchmark problems are freq...
Multi-objective optimization problems are often subject to the presence of objectives that require e...
Many real-world optimization problems are subject to uncertainty. A possible goal is then to find a ...
In dynamic multiobjective optimization problems, the environmental parameters change over time, whic...
This project compares the quality of the distributions of solutions produced by various popular and ...
Robust optimization tries to find flexible solutions when solving problems with uncertain scenarios ...
Optimizing multiple conflicting objectives results in more than one optimal solution (known as Paret...
Robust multi-objective optimization has emerged as an active research. A recent study proposed two d...
Published online: 26 October 2013This paper presents a new approach to robustness analysis in multi-...
This paper presents a new approach to robustness analysis in multi-objective optimization problems a...
This work discusses robustness assessment during multi-objective optimization with a Multi-Objective...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
In real-world applications, it is often desired that a solution is not only of high performance, but...
Jin Y, Sendhoff B. Trade-Off between Performance and Robustness: An Evolutionary Multiobjective Appr...
In optimization studies including multi-objective optimization, the main focus is usually placed in ...
In order to evaluate the relative performance of optimization algorithms benchmark problems are freq...
Multi-objective optimization problems are often subject to the presence of objectives that require e...
Many real-world optimization problems are subject to uncertainty. A possible goal is then to find a ...
In dynamic multiobjective optimization problems, the environmental parameters change over time, whic...
This project compares the quality of the distributions of solutions produced by various popular and ...
Robust optimization tries to find flexible solutions when solving problems with uncertain scenarios ...
Optimizing multiple conflicting objectives results in more than one optimal solution (known as Paret...
Robust multi-objective optimization has emerged as an active research. A recent study proposed two d...