In this study, the parameter free Jaya algorithm (PFJA) is developed for sizing and layout optimization of truss structures subject to natural frequency constraints. The distinctive feature of PFJA is that it uses neither algorithm-specific parameters nor common parameters in the search process. Besides using an elitist strategy where new structural analyses are performed only if strictly necessary, PFJA adaptively changes population size in the optimization process. The validity of proposed PFJA is demonstrated by solving eight classical truss weight minimization problems including up to 59 sizing and layout design variables. The results obtained by the PFJA are compared with those of standard JA, modified Jaya algorithm (MJA) and other state-of-art metaheuristic algorithms in terms of optimized weight, convergence speed and several statistical parameters. Optimization results prove the superiority of PFJA over standard JA, MJA and other metaheuristic optimizers available in the literature.

在这项研究中，无参数Jaya算法（PFJA）被开发用于受自然频率约束的桁架结构的尺寸和布局优化。PFJA的独特之处在于它在搜索过程中既不使用特定于算法的参数也不使用公共参数。PFJA除了使用仅在严格必要时才执行新结构分析的精英策略之外，PFJA在优化过程中会自适应地更改总体大小。通过解决八个经典桁架重量最小化问题（包括多达59个尺寸和布局设计变量），可以证明所提出的PFJA的有效性。通过PFJA获得的结果与标准JA，改进的Jaya算法（MJA）和其他最新的元启发式算法的结果在优化权重方面进行了比较，收敛速度和几个统计参数。优化结果证明了PFJA优于标准JA，MJA和文献中提供的其他元启发式优化器。