This paper proposes a novel metaheuristic framework using a Differential Evolution (DE) algorithm with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Both algorithms are combined employing a collaborative strategy with sequential execution, which is called DE-NSGA-II. The DE-NSGA-II takes advantage of the exploration abilities of the multi-objective evolutionary algorithms strengthened with the ability to search global mono-objective optimum of DE, that enhances the capability of finding those extreme solutions of Pareto Optimal Front (POF) difficult to achieve. Numerous experiments and performance comparisons between different evolutionary algorithms were performed on a referent problem for the mono-objective and multi-objective...
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA)...
Real-world problems often involve the optimisation of multiple conflicting objectives. These problem...
Optimal design of a multi-speed gearbox involves different types of decision variables and objective...
AbstractTo improve performances of multi-objective optimization algorithms, such as convergence and ...
In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical componen...
Optimization is necessary for finding appropriate solutions to a range of real life problems. Evolut...
this paper, we briefly outline the principles of multi-objective optimization. Thereafter, we discus...
This paper considers the problem of constrained multi-objective non-linear optimization of planetary...
Evolutionary algorithms (EAs) are well-known optimization approaches to deal with nonlinear and comp...
[EN] This paper shows a genetic algorithm (GA)-based optimization procedure for gear trains design...
Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteri...
Abstract: Multi-objective EAs (MOEAs) are well established population-based techniques for solving v...
We have developed new multi-objective evolutionary algorithms to improve convergence and diversity o...
Differential evolution (DE) research for multi-objective optimization can be divided into proposals ...
Many engnieering design tasks involve optimising several conflicting goals; these types of problem a...
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA)...
Real-world problems often involve the optimisation of multiple conflicting objectives. These problem...
Optimal design of a multi-speed gearbox involves different types of decision variables and objective...
AbstractTo improve performances of multi-objective optimization algorithms, such as convergence and ...
In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical componen...
Optimization is necessary for finding appropriate solutions to a range of real life problems. Evolut...
this paper, we briefly outline the principles of multi-objective optimization. Thereafter, we discus...
This paper considers the problem of constrained multi-objective non-linear optimization of planetary...
Evolutionary algorithms (EAs) are well-known optimization approaches to deal with nonlinear and comp...
[EN] This paper shows a genetic algorithm (GA)-based optimization procedure for gear trains design...
Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteri...
Abstract: Multi-objective EAs (MOEAs) are well established population-based techniques for solving v...
We have developed new multi-objective evolutionary algorithms to improve convergence and diversity o...
Differential evolution (DE) research for multi-objective optimization can be divided into proposals ...
Many engnieering design tasks involve optimising several conflicting goals; these types of problem a...
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA)...
Real-world problems often involve the optimisation of multiple conflicting objectives. These problem...
Optimal design of a multi-speed gearbox involves different types of decision variables and objective...