Multi-objective heat transfer search algorithm for truss optimization

Author(s):  
Ghanshyam G. Tejani ◽  
Sumit Kumar ◽  
Amir H. Gandomi
2017 ◽  
Vol 8 (3) ◽  
pp. 1-23 ◽  
Author(s):  
Ghanshyam Tejani ◽  
Vimal Savsani ◽  
Vivek Patel

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.


Author(s):  
Sumit Kumar ◽  
Ghanshyam G. Tejani ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat

2019 ◽  
Vol 8 (4) ◽  
pp. 9465-9471

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance


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