Work

Cross Opposition Based Differential Evolution Optimization

Year: 2019

Type: article

Abstract: Differential Evolutionary (DE) Algorithms is one of the most popular metaheuristic approach. For optimization purpose DE is very useful to solve various kind of problems. In addition to that the paper offers a Cross-Opposition Based Differential Evolution (CODE). An impression of Opposition-based learning (OBL) is incorporated in population initialization phase and in step of crossover. The performance of algorithm is analysed for different mutation strategies of DE and various other existing approaches. Results demonstrated that the algorithm outperform in terms of convergence speed, versatile population and dimension size.

Source: International Journal of Recent Technology and Engineering (IJRTE)

DOI: 10.35940/ijrte.b2283.078219

Authors: Shweta Sharma, Ashwani Kumar Yadav, Deepak Sinwar, Bhagyashri Naruka, Vaishali

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4248117346

FWCI:

Cites:

Cited by: 1

Related to: 10