Computational Intelligence in Circuit Synthesis
This paper is devoted to the synthesis of combinational logic circuits through computational intelligence or, more precisely, using evolutionary computation techniques. Are studied two evolution- ary algorithms, the Genetic and the Memetic Algo- rithm (GAs, MAs) and one swarm intelligence algo- rithm, the Particle Swarm Optimization (PSO). GAs are optimization and search techniques based on the principles of genetics and natural selection. MAs are evolutionary algorithms that include a stage of indi- vidual optimization as part of its search strategy, be- ing the individual optimization in the form of a local search. The PSO is a population-based search algo- rithm that starts with a population of random solu- tions called particles. This paper presents the results for digital circuits design using the three above algo- rithms. The results show the statistical characteristics of this algorithms with respect to the number of gen- erations required to achieve the solutions. The article analyzes also a new fitness function that includes an er- ror discontinuity measure, which demonstrated to im- prove significantly the performance of the algorithm.