Hosseini, Eghbal and Sadiq, Ali Safaa and Ghafoor, Kayhan Zrar and Rawat, Danda B and Saif, Mehrdad and Yang, Xinan (2021) Volcano eruption algorithm for solving optimization problems. Neural Computing and Applications, 33 (7). pp. 2321-2337. DOI https://doi.org/10.1007/s00521-020-05124-x
Hosseini, Eghbal and Sadiq, Ali Safaa and Ghafoor, Kayhan Zrar and Rawat, Danda B and Saif, Mehrdad and Yang, Xinan (2021) Volcano eruption algorithm for solving optimization problems. Neural Computing and Applications, 33 (7). pp. 2321-2337. DOI https://doi.org/10.1007/s00521-020-05124-x
Hosseini, Eghbal and Sadiq, Ali Safaa and Ghafoor, Kayhan Zrar and Rawat, Danda B and Saif, Mehrdad and Yang, Xinan (2021) Volcano eruption algorithm for solving optimization problems. Neural Computing and Applications, 33 (7). pp. 2321-2337. DOI https://doi.org/10.1007/s00521-020-05124-x
Abstract
Meta-heuristic algorithms have been proposed to solve several optimization problems in different research areas due to their unique attractive features. Traditionally, heuristic approaches are designed separately for discrete and continuous problems. This paper leverages the meta-heuristic algorithm for solving NP-hard problems in both continuous and discrete optimization fields, such as nonlinear and multi-level programming problems through extensive simulations of volcano eruption process. In particular, a new optimization solution named volcano eruption algorithm is proposed in this paper, which is inspired from the nature of volcano eruption. The feasibility and efficiency of the algorithm are evaluated using numerical results obtained through several test problems reported in the state-of-the-art literature. Based on the solutions and number of required iterations, we observed that the proposed meta-heuristic algorithm performs remarkably well to solve NP-hard problem. Furthermore, the proposed algorithm is applied to solve some large-size benchmarking LP and Internet of vehicles problems efficiently.
Item Type: | Article |
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Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematical Sciences, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 08 Oct 2020 14:41 |
Last Modified: | 06 Jan 2022 14:15 |
URI: | http://repository.essex.ac.uk/id/eprint/28639 |
Available files
Filename: NCAA-D-19-02058 (1).pdf