These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industria...
Design of complex engineering systems often involves multiple interacting disciplines and analyses. ...
The use of Evolutionary Algorithms (EAs) in difficult problems, where the search space is unknown, u...
The objective of this dissertation is to develop a multi-resolution optimization strategy based on t...
These lecture notes highlight some of the recent applications of multi-objective and multidisciplina...
The purpose of this chapter is to give an overview of evolutionary algorithms and describe a particu...
This paper reviews recent progress made in Evolutionary Algorithms (EAs) for single, multiobjective ...
This paper reviews recent progress made in Evolutionary Algorithms (EAs) for single, multi-objective...
This paper describes the formulation and application of a design framework that supports the complex...
International audienceThis paper describes a unified view of parallel evolutionary algorithms for mu...
This paper describes a parallel multi-criteria (multi-objective) evolutionary algorithm for aero-str...
Many complex aeronautical design problems can be formulated with efficient multi-objective evolution...
Many complex aeronautical design problems can be formulated with efficient multi-objective evolution...
This chapter explores the potential merit of an innovative parallel evolutionary algorithm (EA) coup...
The implementation and use of a framework in which engineering optimization problems can be analysed...
AbstractThis paper presents the recent developments in hierarchical genetic algorithms (HGAs) to spe...
Design of complex engineering systems often involves multiple interacting disciplines and analyses. ...
The use of Evolutionary Algorithms (EAs) in difficult problems, where the search space is unknown, u...
The objective of this dissertation is to develop a multi-resolution optimization strategy based on t...
These lecture notes highlight some of the recent applications of multi-objective and multidisciplina...
The purpose of this chapter is to give an overview of evolutionary algorithms and describe a particu...
This paper reviews recent progress made in Evolutionary Algorithms (EAs) for single, multiobjective ...
This paper reviews recent progress made in Evolutionary Algorithms (EAs) for single, multi-objective...
This paper describes the formulation and application of a design framework that supports the complex...
International audienceThis paper describes a unified view of parallel evolutionary algorithms for mu...
This paper describes a parallel multi-criteria (multi-objective) evolutionary algorithm for aero-str...
Many complex aeronautical design problems can be formulated with efficient multi-objective evolution...
Many complex aeronautical design problems can be formulated with efficient multi-objective evolution...
This chapter explores the potential merit of an innovative parallel evolutionary algorithm (EA) coup...
The implementation and use of a framework in which engineering optimization problems can be analysed...
AbstractThis paper presents the recent developments in hierarchical genetic algorithms (HGAs) to spe...
Design of complex engineering systems often involves multiple interacting disciplines and analyses. ...
The use of Evolutionary Algorithms (EAs) in difficult problems, where the search space is unknown, u...
The objective of this dissertation is to develop a multi-resolution optimization strategy based on t...