Immune Cloning Optimization Algorithm Based on Antibody Similarity Screening and Steady-State Adjustment

Liu, Suodong; Tao, Lihua; Liu, Chao; Gao, Yunqiang; Sun, Hongwei; Yuan, Mingxin

doi:10.1145/3503047.3503113

Cited by 2 publications

(8 citation statements)

References 7 publications

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“…In the iterative process of optimization, if the randomly generated complementary antibody groups are not constrained and modified, the algorithm will fall into a local optimum and the evolution speed will be slowed down. So, the immune clonal optimization algorithm based on antibody similarity screening and steady-state adjustment (ICOABAS) [22] is introduced in this paper. Compared with the basic immune clonal optimization algorithm, ICOABAS mainly improves its search efficiency by screening high-similarity antibodies in the antibody population of the welding sequence and improves its global optimization ability by vaccinating the population with a median-based high-quality vaccine.…”

Section: Description Of the Basic Immune Clonal Optimization Algorithmmentioning

confidence: 99%

Immune Optimization of Double-Sided Welding Sequence for Medium-Small Assemblies in Ships Based on Inherent Strain Method

Shen

Liu

Yuan

et al. 2022

Metals

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The double-sided welding process is widely used in ship construction due to its high welding efficiency and forming quality. In order to further reduce the deformation caused by double-sided welding for medium-small assemblies in ships, the optimization of the double-sided welding sequence based on an artificial immune algorithm is carried out. First, the formation mechanism of welding deformation under the double-sided welding process is analyzed by the inherent strain method; next, the reduction of the welding deformation is taken as the optimization goal, and the welding sequence optimization model for double-sided welding is constructed; then, an immune clonal optimization algorithm based on similar antibody similarity screening and steady-state adjustment is introduced, and the immune optimization process for double-sided welding sequence is designed; finally, double-sided welding sequence optimization tests are carried out for four different types of medium-small assemblies in ships. Numerical test results show that, compared with IGA (Immune genetic algorithm), ICA (Immune clonal algorithm), and GA (Genetic algorithm), the maximum welding deformation caused by the welding sequence optimized by the proposed immune clonal algorithm is reduced by 2.4%, 2.8, and 3.3%, respectively, the average maximum welding deformation is reduced by 2.6%, 2.5, and 3.4%, respectively, and the convergence generation is reduced by 16.2%, 13.4, and 11.2%, respectively, which verifies the strong optimization ability and high optimization efficiency of the immune clonal algorithm introduced in the double-sided welding sequence optimization.

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Section: Description Of the Basic Immune Clonal Optimization Algorithmmentioning

confidence: 99%

Immune Optimization of Double-Sided Welding Sequence for Medium-Small Assemblies in Ships Based on Inherent Strain Method

Shen

Liu

Yuan

et al. 2022

Metals

Self Cite

View full text Add to dashboard Cite

show abstract

“…Obviously, it is not only unrealistic to determine the welding sequence by the enumeration method, but it also cannot obtain the optimal solution. Therefore, an immune clonal optimization algorithm based on antibody similarity screening and steady-state adjustment (ICOABAS) [23] is introduced to improve the optimization performance of the welding sequence. The improved immune clonal algorithm mainly improves its search efficiency by screening high similarity antibodies in the welding sequence antibody group; at the same time, it improves its global optimization ability by vaccinating the population based on the median of high-quality vaccination.…”

Section: Construction Of the Finite Element Model For Arc Weld Seammentioning

confidence: 99%

“…In order to facilitate the design of the welding sequence optimization process based on ICOABAS, the basic description of each operator is given first, and the specific definitions can be found in [23].…”

Section: Construction Of the Finite Element Model For Arc Weld Seammentioning

confidence: 99%

“…, a i is a sequence of l-dimensional decimal numbers, and n is the population size, then the antibody clonal operator T c c [23,24] can be described as:…”

Section: Antibody Clonal Operator T C Cmentioning

confidence: 99%

“…According to the mutation probability p m , a small perturbation is randomly applied to the antibody gene position. The antibody mutation operator T m c [23] can be described as:…”

Section: Antibody Mutation Operator T M Cmentioning

confidence: 99%

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Immune Optimization of Welding Sequence for Arc Weld Seams in Ship Medium-Small Assemblies

et al. 2022

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The arc weld seam is a common form in ship medium-small assemblies. In order to reduce the deformation of the welded parts with an arc weld seam, and then improve the welding quality, research on the optimization of welding sequences based on the artificial immune algorithm is carried out in this paper. First, the formation mechanism of welding deformation is analyzed by the thermo-elastic-plastic finite element method; next, the reduction in the welding deformation is taken as the optimization goal, and the welding sequence optimization model for the arc weld seam is constructed under the condition of boundary constraints; then, an immune clonal optimization algorithm based on similar antibody similarity screening and steady-state adjustment is proposed, and its welding sequence optimization ability is improved through antibody screening and median adjustment. Finally, the welding sequence optimization tests are carried out based on the Ansys platform. Numerical tests of a typical arc weld seam show that different welding sequences will cause different welding deformations, which verifies the importance of welding sequence optimization. Furthermore, the numerical test results of four different types of welds in ship medium-small assemblies demonstrated that the use of distributed optimization algorithms for welding sequence optimization can help reduce the amount of welding deformations, and the immune clonal algorithm, based on antibody similarity screening and steady-state adjustment, achieves the optimal combination of the welding sequence. Compared with the other three optimization algorithms, the maximum welding deformation caused by the welding sequence optimized by the proposed immune clonal algorithm is reduced by 3.1%, 4.0%, and 3.4%, respectively, the average maximum welding deformation is reduced by 3.5%, 5.5%, and 4.7%, respectively, and the convergence generation of the optimization algorithm is reduced by 16.8%, 13.1% and 14.5%, respectively, which further verifies the effectiveness and superiority of the proposed immune clonal algorithm in the optimization of welding sequences.

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Immune Cloning Optimization Algorithm Based on Antibody Similarity Screening and Steady-State Adjustment

Cited by 2 publications

References 7 publications

Immune Optimization of Double-Sided Welding Sequence for Medium-Small Assemblies in Ships Based on Inherent Strain Method

Immune Optimization of Double-Sided Welding Sequence for Medium-Small Assemblies in Ships Based on Inherent Strain Method

Immune Optimization of Welding Sequence for Arc Weld Seams in Ship Medium-Small Assemblies

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