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Evolutionary Multi-objective optimization using Genetic Algorithms (GA) are proven more powerful and efficient methods for optimization of complex digital circuit problems. In this paper, Genetic programming (GP) has been used based on GA to automate the design of the Digital Combinational Circuit. It is desired to minimize the total number of gates used and number of generations for evolved circuit...
Evolutionary Algorithm (EA) methods are proved more effective for solving complex digital circuit design problems and evaluating the fitness of combinational circuits. They optimize circuits in terms of less number of gates and transistors. In the proposed method, we have calculated the best fitness of the circuit from the designed algorithm by adjusting the parameters of Genetic Algorithm (GA) like...
A genetic programming-based circuit synthesis method is proposed that enables to globally optimize the number of gates in circuits that have already been synthesized using common methods such as ABC and SIS. The main contribution is a proposal for a new fitness function that enables to significantly reduce the fitness evaluation time in comparison to the state of the art. The fitness function performs...
The field of digital systems has undergone a major revolution in recent decades. Circuits are shrinking in physical size while growing both in speed and range of capabilities. This rapid advancement is not without serious problems, however. Especially worrisome are verification and testing, which become more important as the system complexity increases and time-to-market decreases. Genetic algorithms...
This work investigates the application of cultural algorithms in the field of evolutionary electronics. Cultural Algorithms is an evolutionary model inspired by the cultural evolution process which shows many excellent characteristics and has succeeded in solving some complicated problems. Based on the population space in which individual evolves, the belief space is constructed, in which effective...
The Wireless Sensor Networks (WSN) technology is employed in the open-pit mine slope detection system. When the open-pit mine slope is found abnormal, the WSN transmit data to the monitors timely in case of the unnecessary losses. Quantum genetic algorithm (QGA) is used in the multi-objective optimization problem of slope detection with WSN. It's for designing networking strategy of slope detection...
Quantum teleportation is a typical quantum circuit. We choose it as a benchmark circuit for the problem of quantum circuit synthesis. Genetic algorithm is introduced to synthesis the circuit. A simple coding scheme and the corresponding fitness function are proposed. The algorithm is implemented using Matlab's GA toolbox, and an optimized circuit structure is obtained.
This paper applies a standard genetic algorithm to the optimization of the quantum circuits. We propose a new coding scheme, which encodes quantum gates as integers and stores circuit topology information in the position of the integers. The design of the corresponding fitness function and genetic operators are also discussed. The quantum teleportation circuit, a typical quantum computation process,...
This paper investigates the adequacy of a general form of fitness function, based on a state-based specification, by characterizing the associated search problem and the dynamics of the applied metaheuristic. The measurement approach of the fitness landscape is experimented on various examples and suggests some tuning choices to be made for the metaheuristic considered.
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