Weighted superposition attraction-repulsion (WSAR) algorithm for truss optimization with multiple frequency constraints

An enhanced symbiotic organisms search (ESOS) algorithm is developed and presented. Modifications to the basic symbiotic organisms search algorithm are carried out in all three phases of the algorithm with the aim of balancing the exploitation and exploration capabilities of the algorithm. To verify validity and capability of the ESOS algorithm in solving general optimization problems, the CEC2014 set of 22 benchmark functions is first optimized and the results are compared with other metaheuristic algorithms. The ESOS algorithm is then used to optimize the sizing and shape of five benchmark trusses with multiple frequency constraints. The best (minimum) mass, mean mass, standard deviation of the mass, total number of function evaluations, and the values of frequency constraints are then compared with those of a number of other metaheuristic solutions available in the literature. It is shown that the proposed ESOS algorithm is generally more efficient in optimizing the shape and sizing of trusses with dynamic frequency constraints compared to other reported metaheuristic algorithms, including the basic symbiotic organisms search and its other recently proposed improved variants such as the improved symbiotic organisms search algorithm (ISOS) and modified symbiotic organisms search algorithm (MSOS).

Download Full-text

Hypotrochoid spiral optimization approach for sizing and layout optimization of truss structures with multiple frequency constraints

Engineering With Computers ◽

10.1007/s00366-018-0675-6 ◽

2018 ◽

Vol 35 (4) ◽

pp. 1443-1462 ◽

Cited By ~ 5

Author(s):

A. Kaveh ◽

S. Mahjoubi

Keyword(s):

Layout Optimization ◽

Truss Structures ◽

Optimization Approach ◽

Multiple Frequency ◽

Frequency Constraints

Download Full-text

Modified Sub-Population Based Heat Transfer Search Algorithm for Structural Optimization

International Journal of Applied Metaheuristic Computing ◽

10.4018/ijamc.2017070101 ◽

2017 ◽

Vol 8 (3) ◽

pp. 1-23 ◽

Cited By ~ 7

Author(s):

Ghanshyam Tejani ◽

Vimal Savsani ◽

Vivek Patel

Keyword(s):

Heat Transfer ◽

Optimization Problems ◽

Search Algorithm ◽

Optimal Solution ◽

Population Based ◽

Truss Optimization ◽

Feasible Region ◽

Frequency Constraints ◽

Local Optimal Solution ◽

Better Than

In this study, a modified heat transfer search (MHTS) algorithm is proposed by incorporating sub-population based simultaneous heat transfer modes viz. conduction, convection, and radiation in the basic HTS algorithm. However, the basic HTS algorithm considers only one of the modes of heat transfer for each generation. The multiple natural frequency constraints in truss optimization problems can improve the dynamic behavior of the structure and prevent undesirable vibrations. However, shape and size variables subjected to frequency constraints are difficult to handle due to the complexity of its feasible region, which is non-linear, non-convex, implicit, and often converging to the local optimal solution. The viability and effectiveness of the HTS and MHTS algorithms are investigated by six standard trusses problems. The solutions illustrate that the MHTS algorithm performs better than the HTS algorithm.

Download Full-text