In real-world optimisation problems, feasibility of solutions is invariably an essential requirement. A natural way to deal with feasibility is to cast it as an additional objective in a multi-objective optimisation setting. In this paper, we consider two possible ways to do this, using a multi-level scheme for ranking solutions. One strategy considers feasibility first, before considering objective values, while the other reverses this ordering. The first strategy has been explored before, while the second has not. Experiments show that the second strategy can be much more successful on some difficult problems
Abstract—Multiobjective optimization problems have been widely addressed using evolutionary computat...
Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorith...
Multi-objective optimization problems having more than three objectives are referred to as many-obje...
The framework of multiobjective optimization is used to tackle the multicriteria ranking problem. Th...
Abstract — In optimization, multiple objectives and con-straints cannot be handled independently of ...
In optimization, multiple objectives and constraints cannot be handled independently of the underlyi...
This paper introduces a method for constrained optimization using a modified multi-objective algorit...
AbstractTwo methods for ranking of solutions of multi objective optimization problems are proposed i...
Abstract- Multi-objective evolutionary algorithms are widely established and well developed for prob...
International audienceThis paper proposes a new multi-objective genetic algorithm, called GAME, to s...
International audienceEvolutionary Multi-objective optimization is a popular tool to generate a set ...
In this paper, the interest is on cases where assessing the goodness of a solution for the problem i...
This study overcomes the three major difficulties experienced by the existing multi-objective evolut...
Both objective optimization and constraint satisfaction are crucial for solving constrained multi-ob...
In many practical situations the decision-maker has to pay special attention to decision space to de...
Abstract—Multiobjective optimization problems have been widely addressed using evolutionary computat...
Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorith...
Multi-objective optimization problems having more than three objectives are referred to as many-obje...
The framework of multiobjective optimization is used to tackle the multicriteria ranking problem. Th...
Abstract — In optimization, multiple objectives and con-straints cannot be handled independently of ...
In optimization, multiple objectives and constraints cannot be handled independently of the underlyi...
This paper introduces a method for constrained optimization using a modified multi-objective algorit...
AbstractTwo methods for ranking of solutions of multi objective optimization problems are proposed i...
Abstract- Multi-objective evolutionary algorithms are widely established and well developed for prob...
International audienceThis paper proposes a new multi-objective genetic algorithm, called GAME, to s...
International audienceEvolutionary Multi-objective optimization is a popular tool to generate a set ...
In this paper, the interest is on cases where assessing the goodness of a solution for the problem i...
This study overcomes the three major difficulties experienced by the existing multi-objective evolut...
Both objective optimization and constraint satisfaction are crucial for solving constrained multi-ob...
In many practical situations the decision-maker has to pay special attention to decision space to de...
Abstract—Multiobjective optimization problems have been widely addressed using evolutionary computat...
Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorith...
Multi-objective optimization problems having more than three objectives are referred to as many-obje...