The approaches to tackling optimization problems of multiple-objectives can be classified into 3 categories. In the first category, a problem of n number of objectives is formulated as an «-stage problem with each stage being a single objective problem. At each stage, the technique will concentrate on searching for the best point to achieve a particular objective. For the second category of techniques, all the objectives of a problem are considered together with the goal of finding a good solution which achieves all the objectives simultaneously. The third category of approaches involves finding all the efficient solutions or non-inferior solutions from which the solution is chosen.Doctor of Philosophy (EEE
Abstract — In optimization, multiple objectives and con-straints cannot be handled independently of ...
A number of researchers have successfully integrated stochastic computer simulation models with comb...
This research aims to show the performance of some genetic multi-goals algorithms, especially those ...
Multi-objectivization is the process of reformulating a single-objective problem into a multi-object...
This study presents a new approach to solve multi-response simulation optimization problems. This ap...
Evolution strategies --- a stochastic optimization method originally designed for single criterion p...
Some non-linear optimisation problems are difficult to solve by con-ventional hill-climbing methods,...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
Multi-objective optimization problems having more than three objectives are referred to as many-obje...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Practical optimization problems often have multiple objectives, which are likely to conflict with ea...
Multi-objective (MO) optimization problems deal with multiple conflicting objectives at the same tim...
In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA)...
In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA)...
Abstract — In optimization, multiple objectives and con-straints cannot be handled independently of ...
A number of researchers have successfully integrated stochastic computer simulation models with comb...
This research aims to show the performance of some genetic multi-goals algorithms, especially those ...
Multi-objectivization is the process of reformulating a single-objective problem into a multi-object...
This study presents a new approach to solve multi-response simulation optimization problems. This ap...
Evolution strategies --- a stochastic optimization method originally designed for single criterion p...
Some non-linear optimisation problems are difficult to solve by con-ventional hill-climbing methods,...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
Multi-objective optimization problems having more than three objectives are referred to as many-obje...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Practical optimization problems often have multiple objectives, which are likely to conflict with ea...
Multi-objective (MO) optimization problems deal with multiple conflicting objectives at the same tim...
In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA)...
In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA)...
Abstract — In optimization, multiple objectives and con-straints cannot be handled independently of ...
A number of researchers have successfully integrated stochastic computer simulation models with comb...
This research aims to show the performance of some genetic multi-goals algorithms, especially those ...