Recent Developments in Derivative-free Multiobjective Optimization
نویسندگان
چکیده
In practical applications it is common to have several conflicting objective functions to optimize. Frequently, these functions are nondifferentiable or discontinuous, could be subject to numerical noise and/or be of black-box type, preventing the use of derivative-based techniques. In this paper we give an overview of some recent developments in Derivative-free Multiobjective Optimization. We introduce the basic concepts and ideas commonly considered for the algorithmic development in Multiobjective Optimization and review some recent classes of methods which do not make use of derivatives. In particular, we will focus on Direct Search Methods (DSM) of directional type and Evolutionary Multiobjective Optimization (EMO).
منابع مشابه
Multiglods: Global and Local Multiobjective Optimization Using Direct Search
The optimization of multimodal functions is a challenging task, in particular when derivatives are not available for use. Recently, in a directional direct search framework, a clever multistart strategy was proposed for global derivative-free optimization of single objective functions. The goal of the current work is to generalize this approach to the computation of global Pareto fronts for mul...
متن کاملEfficient Simulation and Optimization of Rotationally Symmetric, Converging-Diverging de Laval Nozzles for Twin Wire Arc Spraying
Recent developments in the design of rotationally symmetric, convergingdiverging de Laval nozzles for the use in twin wire arc spraying processes are discussed. Various aspects of an efficient implementation of the proposed gas dynamics solution algorithm on modern multiand many-core architectures are addressed. Finally, a general framework for the application of massively parallel, derivative-...
متن کاملDerivative-Free Pattern Search Methods for Multidisciplinary Design Problems
There have been interesting recent developments in methods for solving optimization problems without making use of derivative (sensitivity) information. While calculus based methods that employ derivative information can be extremely eecient and very eeec-tive, they are not applicable to all MDO problems, for instance, when the function to be optimized is nondiierentiable, when sensitivity info...
متن کاملDerivative - Free Pattern Search Methods forMultidisciplinary Design
There have been interesting recent developments in methods for solving optimization problems without making use of derivative (sensitivity) information. While calculus based methods that employ derivative information can be extremely eecient and very eeec-tive, they are not applicable to all MDO problems, for instance, when the function to be optimized is nondiierentiable, when sensitivity info...
متن کاملMultiobjective optimization using an adaptive weighting scheme
A new Pareto front approximation method is proposed for multiobjective optimization problems with bound constraints. The method employs a hybrid optimization approach using two derivative free direct search techniques, and intends to solve blackbox simulation based multiobjective optimization problems where the analytical form of the objectives is not known and/or the evaluation of the objectiv...
متن کامل