A modified niching crow search approach to well placement optimization

• Main Authors: Islam, J., Rahaman, M.S.A., Vasant, P.M., Negash, B.M., Hoqe, A., Alhitmi, H.K., Watada, J.
• Format: Article
• Published: MDPI AG 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106398980&doi=10.3390%2fen14040857&partnerID=40&md5=fdf288e490d86ff03b4695c1174870e6; http://eprints.utp.edu.my/23883/

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.