Improved whale optimization algorithm and its application in vehicle structural crashworthiness

Whale optimization algorithm (WOA) is a novel-innovative swarm-based meta-heuristic algorithm with excellent performance, but it may still be trapped into local extremum for troublesome problems. To this end, an improved multi-objective whale optimization algorithm (IMOWOA) is proposed to cover the...

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Vydáno v:International journal of crashworthiness Ročník 28; číslo 2; s. 202 - 216
Hlavní autoři: Qian, Lijun, Yu, Luxin, Huang, Yuezhu, Jiang, Ping, Gu, Xianguang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cambridge Taylor & Francis 04.03.2023
Taylor & Francis Ltd
Témata:
Algorithms
Competitiveness
Convergence
Crashworthiness
evolution operators
Heuristic methods
Impact strength
Improved multi-objective whale optimization
individual difference
Multiple objective analysis
Optimization
Regression models
Support vector machines
vehicle structural crashworthiness
ISSN:1358-8265, 1754-2111
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Shrnutí:Whale optimization algorithm (WOA) is a novel-innovative swarm-based meta-heuristic algorithm with excellent performance, but it may still be trapped into local extremum for troublesome problems. To this end, an improved multi-objective whale optimization algorithm (IMOWOA) is proposed to cover the shortages. Firstly, in the search stage of WOA, individual difference is considered to strengthen the exploration ability, and evolution operators are introduced to regenerate the stagnated population to prevent premature convergence. Next, the performance of IMOWOA is compared with MOWOA and other classical optimization algorithms, and a series of multi-objective test functions are used. The results on the convergence and diversity of Pareto front confirm that IMOWOA has better feasibility and competitiveness. Finally, integrated with the least squares support vector regression (LSSVR) model, IMOWOA is applied to the deterministic optimization of vehicle structural crashworthiness. The conclusion testified the efficiency of IMOWOA in the field of vehicle crashworthiness.
Bibliografie:ObjectType-Article-1
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ISSN:1358-8265
1754-2111
DOI:10.1080/13588265.2022.2074705