Looking at articles or conference papers published since the turn of the century, Pareto optimization is the dominating assessment method for multi-objective nonlinear optimization problems. However, is it always the method of choice for real-world applications, where either more than four objectives have to be considered, or the same type of task is repeated again and again with only minor modifications, in an automated optimization or planning process? This paper presents a classification of application scenarios and compares the Pareto approach with an extended version of the weighted sum, called cascaded weighted sum, for the different scenarios. Its range of application within the field of multi-objective optimization is discussed as w...
In this study, solutions for multi-objective constrained problems and their fixed weight linearly ag...
AbstractThere exist two general approaches to solve multiple objective problems. The first approach ...
Decomposition-based methods are often cited as the solution to multi-objective nonconvex optimizatio...
Looking at articles or conference papers published since the turn of the century, Pareto optimizatio...
Multiple objective optimization involves the simultaneous optimization of more than one, possibly co...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Optimizing multiple conflicting objectives results in more than one optimal solution (known as Paret...
Multiple objective optimization involves the simultaneous optimization of more than one, possibly co...
Many practical optimization problems usually have several conflicting objectives. In those multi-ob...
Many practical optimization problems usually have several conflicting objectives. In those multi-ob...
Multi-objective formulations are realistic models for many complex engineering optimization problems...
This paper presents a comprehensive review of a multi-objective particle swarm optimization (MOPSO) ...
This work proposes a novel multi-objective optimization approach that globally finds a representativ...
In this study, solutions for multi-objective constrained problems and their fixed weight linearly ag...
AbstractThere exist two general approaches to solve multiple objective problems. The first approach ...
Decomposition-based methods are often cited as the solution to multi-objective nonconvex optimizatio...
Looking at articles or conference papers published since the turn of the century, Pareto optimizatio...
Multiple objective optimization involves the simultaneous optimization of more than one, possibly co...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Many real-world applications of multi-objective optimization involve a large number of objectives. A...
Optimizing multiple conflicting objectives results in more than one optimal solution (known as Paret...
Multiple objective optimization involves the simultaneous optimization of more than one, possibly co...
Many practical optimization problems usually have several conflicting objectives. In those multi-ob...
Many practical optimization problems usually have several conflicting objectives. In those multi-ob...
Multi-objective formulations are realistic models for many complex engineering optimization problems...
This paper presents a comprehensive review of a multi-objective particle swarm optimization (MOPSO) ...
This work proposes a novel multi-objective optimization approach that globally finds a representativ...
In this study, solutions for multi-objective constrained problems and their fixed weight linearly ag...
AbstractThere exist two general approaches to solve multiple objective problems. The first approach ...
Decomposition-based methods are often cited as the solution to multi-objective nonconvex optimizatio...