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Laplacian whale optimization algorithm

  • Amarjeet SinghEmail author
Original Article
  • 58 Downloads

Abstract

Whale optimization algorithm is a new member of nature inspired optimization algorithm which is inspired from foraging behaviour of humpback whales. Similar to other heuristic algorithms, Whale optimization algorithm suffers with immature convergence and stagnation problems while solving optimization problems. In this paper, Whale optimization algorithm is hybridized with Laplace Crossover operator and a new algorithm, Laplacian whale optimization algorithm (LXWOA), has been proposed. It has been used to solve a set of 23 classical benchmark functions which consists of scalable unimodal functions, scalable multimodal functions and low dimensional multimodal functions and the results are compared with original whale optimization algorithm, particle swarm optimization, differential evolution, gravitational search algorithm and Laplacian gravitational search algorithm. In this paper, LXWOA and WOA have also been used to solve the problem of extraction of compounds from gardenia.

Keywords

Whale optimization algorithm Laplace crossover Numerical optimization Heuristic algorithm Gardenia problem 

Notes

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Copyright information

© The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2019

Authors and Affiliations

  1. 1.Department of MathematicsJanki Devi Memorial College, University of Delhi, Sir Ganga Ram Hospital MargNew DelhiIndia

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