In some expensive multiobjective optimization problems, several function evaluations can be carried out at one time. Therefore, it is very desirable to develop methods which can g...
Qingfu Zhang, Wudong Liu, Edward P. K. Tsang, Boto...
This paper describes a noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective fu...
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
We propose the use of a new algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template for single objective optimization to...
Antonio J. Nebro, Francisco Luna, Enrique Alba, Be...
Under mild conditions, it can be induced from the Karush-Kuhn-Tucker condition that the Pareto set, in the decision space, of a continuous multiobjective optimization problem is (m...
— We describe the development and testing of a metaheuristic procedure, based on the scatter search methodology, for the problem of approximating the efficient frontier of nonlin...
This paper presents an algorithm that converges to points that satisfy a first order necessary condition of weakly Pareto solutions of multiobjective optimization problems. Hints ...
Abstract— In this paper, we propose the concept of the flexibility of design variables to Pareto-optimal solutions in MultiObjective Optimization problems. In addition, we intro...
This paper discusses a new model of parallel evolutionary algorithms (EAs) called the specialized island model (SIM) that can be used to generate a set of diverse non-dominated sol...
In this paper, we present an extension of the heuristic called “particle swarm optimization” (PSO) that is able to deal with multiobjective optimization problems. Our approach ...