2020
DOI: 10.28991/cej-2020-03091557
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Improved Wolf Pack Algorithm for Optimum Design of Truss Structures

Abstract: In order to find a more effective method in structural optimization, an improved wolf pack optimization algorithm was proposed. In the traditional wolf pack algorithm, the problem of falling into local optimum and low precision often occurs. Therefore, the adaptive step size search and Levy's flight strategy theory were employed to overcome the premature flaw of the basic wolf pack algorithm. Firstly, the reasonable change of the adaptive step size improved the fineness of the search and effectively accelerate… Show more

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Cited by 7 publications
(3 citation statements)
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“…In our research, a swarm intelligent algorithm named the artificial bee colony algorithm (ABC), which possesses a strong global optimization ability and fewer parameters [11][12][13][14], is firstly proposed to solve the problem of assigning the entrances and exits as well as autonomous ETVs for several outbound and inbound tasks simultaneously. Actually, as an artificial intelligence algorithm, the ABC has been well adapted for various complex optimization and scheduling problems [15][16][17][18][19][20][21]; however, it often suffers from the problem of a slow convergence rate because of its single-dimensional random search strategy in the bee updating phases. To accelerate the convergence speed without reducing the accuracy, other metaheuristic algorithms were introduced and combined with the traditional ABC.…”
Section: Introductionmentioning
confidence: 99%
“…In our research, a swarm intelligent algorithm named the artificial bee colony algorithm (ABC), which possesses a strong global optimization ability and fewer parameters [11][12][13][14], is firstly proposed to solve the problem of assigning the entrances and exits as well as autonomous ETVs for several outbound and inbound tasks simultaneously. Actually, as an artificial intelligence algorithm, the ABC has been well adapted for various complex optimization and scheduling problems [15][16][17][18][19][20][21]; however, it often suffers from the problem of a slow convergence rate because of its single-dimensional random search strategy in the bee updating phases. To accelerate the convergence speed without reducing the accuracy, other metaheuristic algorithms were introduced and combined with the traditional ABC.…”
Section: Introductionmentioning
confidence: 99%
“…Kok, Lau, Phan and Ting [26] used GA for optimum steel residential roof truss design with cold-formed sections. Li and Xu [27] developed an improved wolf pack algorithm to optimize truss structures. Some of the recent challenges in the structural optimization area are modified subpopulation teaching–learning-based algorithms for topology optimization of truss problems [28] , optimum structural design by the adaptive version of the symbiotic organisms search (SOS) method [29] , topology optimization with different metaheuristics [30] , Structural Optimization with plasma generation optimizer [31] ,and some other research [32] , [33] , [34] , [35] , [36] , [37] , [38] .…”
Section: Introductionmentioning
confidence: 99%
“…Based on the above analysis, the wolf pack algorithm (WPA) was applied to optimize the parameters of LSSVM in this paper. e performance of WPA will not be affected by a small change in parameters and the selection of parameters is relatively easy, so it has a good global convergence and computational robustness, which is suitable for solving the high-dimensional, multipeak complex functions, especially [24].…”
Section: Introductionmentioning
confidence: 99%