A review of multi-objective optimization: methods and algorithms in mechanical engineering problems
JLJ Pereira, GA Oliver, MB Francisco… - … Methods in Engineering, 2022 - Springer
The optimization problems that must meet more than one objective are called multi-objective
optimization problems and may present several optimal solutions. This manuscript brings …
optimization problems and may present several optimal solutions. This manuscript brings …
An overview of evolutionary algorithms in multiobjective optimization
CM Fonseca, PJ Fleming - Evolutionary computation, 1995 - ieeexplore.ieee.org
The application of evolutionary algorithms (EAs) in multiobjective optimization is currently
receiving growing interest from researchers with various backgrounds. Most research in this …
receiving growing interest from researchers with various backgrounds. Most research in this …
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Evolutionary algorithms (EAs) are often well-suited for optimization problems involving
several, often conflicting objectives. Since 1985, various evolutionary approaches to …
several, often conflicting objectives. Since 1985, various evolutionary approaches to …
[图书][B] Evolutionary algorithms for solving multi-objective problems
CAC Coello - 2007 - Springer
Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …
solution has been a challenge to researchers for a long time. Despite the considerable …
Multi-objective optimisation using evolutionary algorithms: an introduction
K Deb - Multi-objective evolutionary optimisation for product …, 2011 - Springer
As the name suggests, multi-objective optimisation involves optimising a number of
objectives simultaneously. The problem becomes challenging when the objectives are of …
objectives simultaneously. The problem becomes challenging when the objectives are of …
Comparison of multiobjective evolutionary algorithms: Empirical results
In this paper, we provide a systematic comparison of various evolutionary approaches to
multiobjective optimization using six carefully chosen test functions. Each test function …
multiobjective optimization using six carefully chosen test functions. Each test function …
[PDF][PDF] Genetic algorithms for multiobjective optimization: formulationdiscussion and generalization.
CM Fonseca, PJ Fleming - Icga, 1993 - Citeseer
The paper describes a rank-based tness assignment method for Multiple Objective Genetic
Algorithms (MOGAs). Conventional niche formation methods are extended to this class of …
Algorithms (MOGAs). Conventional niche formation methods are extended to this class of …
[PDF][PDF] Genetic algorithms and machine learning
JJ Grefenstette - Proceedings of the sixth annual conference on …, 1993 - dl.acm.org
One approach to the design of learning systems is to extract heuristics from existing adaptive
systems. Genetic algorithms are heuristic learning models based on principles drawn from …
systems. Genetic algorithms are heuristic learning models based on principles drawn from …
[图书][B] Genetic algorithms and engineering optimization
A comprehensive guide to a powerful new analytical tool by two of its foremost innovators
The past decade has witnessed many exciting advances in the use of genetic algorithms …
The past decade has witnessed many exciting advances in the use of genetic algorithms …
Optimization of control parameters for genetic algorithms
JJ Grefenstette - IEEE Transactions on systems, man, and …, 2007 - ieeexplore.ieee.org
The task of optimizing a complex system presents at least two levels of problems for the
system designer. First, a class of optimization algorithms must be chosen that is suitable for …
system designer. First, a class of optimization algorithms must be chosen that is suitable for …