Tend type compact genetic algorithm (GA) based on non-durable elitism strategy

Abstract

The present invention discloses a tend type compact GA based on a non-durable elitism strategy. The tend type compact GA based on the non-durable elitism strategy comprises the steps of constructing a probability vector P same as a chromosome coding length L, valuating each position of the probability vector as 0.5, and then enabling the probability vector to generate two chromosomes randomly; calculating the fitness values of the generated two chromosomes separately, and comparing the two fitness values to decide a winner and a loser; comparing each position of the generated two chromosomes, and updating the probability vector according to the fitness values; determining whether an algorithm execution result reaches a convergence condition; if the algorithm execution result does not reach a convergence condition, carrying out the mutation operation on the chromosomes; introducing the non-durable elitism strategy and a parameter alpha, and determining the generation numbers of the elitism; if the algorithm execution result reaches the convergence condition, ending the algorithm. According to the present invention, the convergence efficiency of the algorithm is improved, the searching capability is strong, the occupied resource is few, and a good application effect is obtained in the hardware evolution.

Description

technical field [0001] The invention belongs to the technical field of evolutionary hardware, and in particular relates to a trending compact GA method based on a non-durable elite retention strategy. Background technique [0002] After fixed-function hardware and reconfigurable hardware, the next generation of hardware will be self-configurable and evolving hardware, that is, Evolvable Hardware (EHW for short), which uses biological development models to solve large and complex problems. The idea of ​​evolutionary hardware comes from the idea of ​​developing machines with self-reproduction and self-repair capabilities proposed by the father of computer John Von Neumann in the 1950s. Due to the fast parallelism of the hardware itself, the evolutionary hardware can search in the design space and realize the design automation, which has become one of the research hotspots in the field of computer system architecture and electronic design automation. Evolutionary hardware refe...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a trending compact GA method based on non-durable elite retention strategy, aiming to solve the problem of slow evolution speed, low evolution efficiency, low evolution circuit robustness, and the circuit scale that can be handled in current evolution hardware technology. and a limited variety of questions

Images