In this paper, an algorithm inspired from quantum evolution and particle swarm to evolve combinational logic circuits is presented. This algorithm uses the framework of the local version of particle swarm optimization with quantum evolutionary algorithms, and integer encoding. A multi-objective fitness function is used to evolve the combinational logic circuits in order obtain feasible circuits with minimal number of gates in the design. A comparative study indicates the superior performance of the hybrid quantum evolution-particle swarm inspired algorithm over the particle swarm and other evolutionary algorithms (such as genetic algorithms) independently
In this paper, a generalization of the original Quantum-Inspired Evolutionary Algorithm (QIEA): the ...
Particle Swarm Optimization (PSO) is a population-based search algorithm that is initialized with a ...
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophistic...
Particle swarm optimization (PSO) motivated by the social behavior of organisms is proposed for evol...
This paper presents the evolution of combinational logic circuits by a new hybrid algorithm known as...
This paper presents two evolutionary schemes and a swarm intelligence algorithm for the design of co...
Evolutionary computation (EC) is a growing research field of Artificial Intelligence (AI) and is div...
Evolutionary Computation (EC) is a growing research field of Artificial Intelligence (AI), particula...
This paper is devoted to the synthesis of combinational logic circuits through computacional intelli...
Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of ...
Abstract—Due to the non- intuitive nature of Quantum algorithms, it becomes difficult for a classica...
Due to the non- intuitive nature of Quantum algorithms, it becomes difficult for a classically train...
Several Evolutionary Algorithms (EAs) are applied in the design and optimization of digital circuits...
We present a new evolutionary algorithm on the basis of quantum computations technology for solving ...
This paper proposes a genetic algorithm for designing combinational logic circuits and studies four ...
In this paper, a generalization of the original Quantum-Inspired Evolutionary Algorithm (QIEA): the ...
Particle Swarm Optimization (PSO) is a population-based search algorithm that is initialized with a ...
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophistic...
Particle swarm optimization (PSO) motivated by the social behavior of organisms is proposed for evol...
This paper presents the evolution of combinational logic circuits by a new hybrid algorithm known as...
This paper presents two evolutionary schemes and a swarm intelligence algorithm for the design of co...
Evolutionary computation (EC) is a growing research field of Artificial Intelligence (AI) and is div...
Evolutionary Computation (EC) is a growing research field of Artificial Intelligence (AI), particula...
This paper is devoted to the synthesis of combinational logic circuits through computacional intelli...
Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of ...
Abstract—Due to the non- intuitive nature of Quantum algorithms, it becomes difficult for a classica...
Due to the non- intuitive nature of Quantum algorithms, it becomes difficult for a classically train...
Several Evolutionary Algorithms (EAs) are applied in the design and optimization of digital circuits...
We present a new evolutionary algorithm on the basis of quantum computations technology for solving ...
This paper proposes a genetic algorithm for designing combinational logic circuits and studies four ...
In this paper, a generalization of the original Quantum-Inspired Evolutionary Algorithm (QIEA): the ...
Particle Swarm Optimization (PSO) is a population-based search algorithm that is initialized with a ...
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophistic...