Add to ORKGIn this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.Department of Electrical Engineerin
In this paper a new class of hybridization strategies between GA and PSO is presented and validated....
Particle swarm optimization (PSO) is a population-based optimization algorithm which has great poten...
This paper introduces a new approach called hybrid particle swarm optimization like algorithm (hybri...
This paper proposes a new method for a modified particle swarm optimization algorithm (MPSO) combine...
International audienceThis paper presents a novel hybrid evolutionary algorithm that combines Partic...
This paper proposes a hybrid particle swarm optimization with the fast-simulated annealing (PSO-FSA)...
Purpose - Meta-heuristic algorithms are efficient in achieving the optimal solution for engineering ...
International audienceIn the structure problems, the randomness and the uncertainties of the distrib...
Particle swarm optimization (PSO) is a simple metaheuristic method to implement with robust performa...
Particle Swarm Optimization (PSO) is a new optimization algorithm, which is applied in many fields w...
Particle swarm optimization (PSO) and Ant Colony Optimization (ACO) are two important methods of sto...
Genetic algorithm is widely used in optimization problems for its excellent global search capabiliti...
The work presented in this PhD thesis contibutes to a new method for a modified particle swarm optim...
Abstract: This paper deals with a new algorithm of a parallel simulated annealing HGSA which include...
A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particl...
In this paper a new class of hybridization strategies between GA and PSO is presented and validated....
Particle swarm optimization (PSO) is a population-based optimization algorithm which has great poten...
This paper introduces a new approach called hybrid particle swarm optimization like algorithm (hybri...
This paper proposes a new method for a modified particle swarm optimization algorithm (MPSO) combine...
International audienceThis paper presents a novel hybrid evolutionary algorithm that combines Partic...
This paper proposes a hybrid particle swarm optimization with the fast-simulated annealing (PSO-FSA)...
Purpose - Meta-heuristic algorithms are efficient in achieving the optimal solution for engineering ...
International audienceIn the structure problems, the randomness and the uncertainties of the distrib...
Particle swarm optimization (PSO) is a simple metaheuristic method to implement with robust performa...
Particle Swarm Optimization (PSO) is a new optimization algorithm, which is applied in many fields w...
Particle swarm optimization (PSO) and Ant Colony Optimization (ACO) are two important methods of sto...
Genetic algorithm is widely used in optimization problems for its excellent global search capabiliti...
The work presented in this PhD thesis contibutes to a new method for a modified particle swarm optim...
Abstract: This paper deals with a new algorithm of a parallel simulated annealing HGSA which include...
A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particl...
In this paper a new class of hybridization strategies between GA and PSO is presented and validated....
Particle swarm optimization (PSO) is a population-based optimization algorithm which has great poten...
This paper introduces a new approach called hybrid particle swarm optimization like algorithm (hybri...