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An Enhanced Differential Evolution Algorithm with New Environmental-Based Parameters for Solving Optimization Problems

  • Avjeet SinghEmail author
  • Alok Kumar
  • Anoj Kumar
Conference paper
  • 62 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1141)

Abstract

体育赛事投注记录for solving the complex and nonlinear problems, there are numerous nature-inspired algorithms exist, and differential evolution (de) is one of the best algorithms. de is utilized in numerous fields of science and engineering. it suffers some drawbacks like, this algorithm suffers from premature convergence rate and furthermore the stagnation problem. this paper presents a novel approach new environmental-based parameter for differential evolution (nepde). in this article, two new variants of de (nepde-b and nepde-cr) have been proposed for solving the stagnation problem and maintaining diversity. this approach improved the performance of the standard differential evolution, and convergence speed is also improved. the candidate’s solutions do not converge to a specific point to the search space. we used cec2015 benchmark functions for measuring the performance of the proposed algorithm, and the results indicate that the proposed approach is able to find effective solutions after comparing the different state-of-the-art algorithms of de.

Keywords

Environmental mutation Evolutionary algorithms Differential evolution 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.MNNIT AllahabadPrayagrajIndia

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