Comparison of recent optimization algorithms for design optimization of a cam-follower mechanism

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This study presents the application of seven recent meta-heuristic optimization algorithms to automate design of disk cam mechanism with translating roller follower regarding four follower motion laws. The algorithms are: salp swarm algorithm (SSA), moth–flame optimization (MFO), ant lion optimizer (ALO), multi verse optimizer (MVO), grey wolf optimizer (GWO), evaporation rate water cycle algorithm (ER-WCA), and mine blast algorithm (MBA). The optimum cam design problem is formulated with three objectives including the minimum congestion, maximum performance, and maximum strength resistance of the cam. Moreover, the effect of selecting follower motion law on the optimal design of mechanism is investigated. The computational results clearly indicate that the utilized algorithms are very competitive in structural design optimization, especially MBA, ER-WCA, MFO and GWO techniques. Among the four follower motion laws, the polynomial 3-4-5 degree is the best one.

论文关键词:Algorithms,Metaheuristics,Optimization,Cam mechanism,Follower motion law,Grey wolf optimizer,Salp Swarm Optimizer,Moth-Flame optimizer,Multi verse optimizer,Ant lion optimizer

论文评审过程:Received 12 January 2019, Revised 11 November 2019, Accepted 12 November 2019, Available online 16 November 2019, Version of Record 8 February 2020.

论文官网地址:https://doi.org/10.1016/j.knosys.2019.105237