Litcius/Paper detail

Proposed Selection Technique of Evolutionary Algorithm and its implementation for Combinatorial Problems

Rajiv Kumar, Minakshi Memoria

202012 citationsDOI

Abstract

The present paper proposed new selection techniques of the evolutionary algorithm. The nature of the evolutionary algorithm is probabilistic and randomized. Evolutionary algorithm work on Charles Darwin's principle of natural selection. This algorithm can be applied to various optimization problems, such as scheduling, traveling salesman problems, Routing problems, or combinatorial problems. Evolutionary algorithms include Genetic algorithm, Memetic algorithm. The performance of the evolutionary algorithm depends upon its operators, such as selection techniques, crossover operators, mutation operator, and its parameter setting. The main focus of this paper is selection techniques. The proposed algorithm has been successfully implemented for the CPU scheduling problem. Experimental results show better results.

Topics & Concepts

Memetic algorithmEvolutionary algorithmCrossoverComputer scienceMathematical optimizationSelection (genetic algorithm)Cultural algorithmEvolutionary computationScheduling (production processes)AlgorithmGenetic operatorGenetic algorithmTravelling salesman problemPopulation-based incremental learningMathematicsArtificial intelligenceScheduling and Optimization AlgorithmsMetaheuristic Optimization Algorithms ResearchConstraint Satisfaction and Optimization