ESA: a hybrid bio-inspired metaheuristic optimization approach for engineering problems

• Published in: Engineering with computers Vol. 37; no. 1; pp. 323 - 353
• Main Author: Dhiman, Gaurav
• Format: Journal Article
• Language: English
• Published: London Springer London 01-01-2021; Springer Nature B.V
• Subjects: Algorithms; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Computer Science; Computer-Aided Engineering (CAD; Control; Heuristic methods; Math. Applications in Chemistry; Mathematical and Computational Engineering; Optimization; Original Article; Sensitivity analysis; Systems Theory; Salp swarm algorithm; Engineering problems; Emperor penguin optimizer; Metaheuristics; Optimization
• ISSN: 0177-0667; 1435-5663
• DOI: 10.1007/s00366-019-00826-w

In this paper, a hybrid bio-inspired metaheuristic optimization approach namely emperor penguin and salp swarm algorithm (ESA) is proposed. This algorithm imitates the huddling and swarm behaviors of emperor penguin optimizer and salp swarm algorithm, respectively. The efficiency of the proposed ESA is evaluated using scalability analysis, convergence analysis, sensitivity analysis, and ANOVA test analysis on 53 benchmark test functions including classical and IEEE CEC-2017. The effectiveness of ESA is compared with well-known metaheuristics in terms of the optimal solution. The proposed ESA is also applied on six constrained and one unconstrained engineering problems to evaluate its robustness. The results reveal that ESA offers optimal solutions as compared to the other competitor algorithms.