The equilibrium optimization algorithm and the response surface-based metamodel for optimal structural design of vehicle components

2020 ◽  
Vol 62 (5) ◽  
pp. 492-496
Author(s):  
Ali Rıza Yıldız ◽  
H. Özkaya ◽  
M. Yıldız ◽  
S. Bureerat ◽  
B. S. Yıldız ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Automotive Industry ◽  
Structural Design ◽  
Optimization Problem ◽  
Low Cost ◽  
Design Problems ◽  
Structural Design Optimization ◽  
Vehicle Components ◽  
Vehicle Seat ◽  
Real World Problems

Abstract Due to harsh competitive conditions and the transition to new vehicles such as hybrid and full-electrical, the interest in the design of light and low-cost vehicles is increasing. In this paper, a recent metaheuristic procedure which is an equilibrium optimization algorithm (EOA) is used to solve a structural design optimization problem for a vehicle seat bracket to prove how the EOA can be used in solving industrial design problems. This paper is the first application of the EAO to real-world problems in the literature. The results strongly prove the capability of the EOA for designing optimum components in the automotive industry.

A novel hybrid marine predators-Nelder-Mead optimization algorithm for the optimal design of engineering problems

2021 ◽  
Vol 63 (5) ◽  
pp. 453-457
Author(s):  
Natee Panagant ◽  
Mustafa Yıldız ◽  
Nantiwat Pholdee ◽  
Ali Rıza Yıldız ◽  
Sujin Bureerat ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Automotive Industry ◽  
Structural Design ◽  
Low Cost ◽  
Design Problems ◽  
Marine Predators ◽  
Nature Inspired Algorithm ◽  
Engineering Problems ◽  
Structural Design Optimization ◽  
Nelder Mead Algorithm

Abstract The marine predators optimization algorithm (MPA) is a recently developed nature-inspired algorithm. In this paper, the Nelder-Mead algorithm is utilized to improve the local exploitation powers of the MPA when described as a hybrid marine predators and Nelder-Mead (HMPANM). Due to the harsh competitive conditions as well as the transition to new vehicles such as hybrid and full-electrical cars, the interest in the design of light and low-cost vehicles is increasing. In this study, a recent metaheuristic addition, a hybrid marine predators optimization algorithm, is used to solve a structural design optimization problem to prove how the HMPANM can be used in solving industrial design problems. The results strongly prove the capability of the HMPANM for the optimum design of components in the automotive industry.

scholarly journals Beetle swarm optimization algorithm: Theory and application

Filomat ◽  
2020 ◽  
Vol 34 (15) ◽  
pp. 5121-5137
Author(s):  
Tiantian Wang ◽  
Long Yang ◽  
Qiang Liu
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Pso Algorithm ◽  
Design Problems ◽  
Swarm Optimization ◽  
Engineering Design Problems ◽  
Grasshopper Optimization Algorithm ◽  
Algorithm Theory ◽  
Grasshopper Optimization ◽  
Practical Impact

In this paper, a new meta-heuristic algorithm, called beetle swarm optimization (BSO) algorithm, is proposed by enhancing the performance of swarm optimization through beetle foraging principles. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization (PSO) algorithm, genetic algorithm (GA) and grasshopper optimization algorithm (GOA). Numerical experiments show that the BSO algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblau?s optimization problem, are also considered and the proposed BSO algorithm is shown to be competitive in those applications.

The equilibrium optimization algorithm and the response surface-based metamodel for optimal structural design of vehicle components

2020 ◽  
Vol 62 (5) ◽  
pp. 492-496 ◽  
Author(s):  
Hüseyin Özkaya ◽  
Mustafa Yıldız ◽  
Ali Rıza Yıldız ◽  
Sujin Bureerat ◽  
Betül Sultan Yıldız ◽  
...  
Keyword(s):  
Response Surface ◽  
Optimization Algorithm ◽  
Structural Design ◽  
Optimal Structural Design ◽  
Vehicle Components

Robust Structural Design Optimization Under Non-Probabilistic Uncertainties

2011 ◽  
Author(s):  
Jiantao Liu ◽  
Hae Chang Gea ◽  
Ping An Du
Keyword(s):  
Structural Optimization ◽  
Design Optimization ◽  
Structural Design ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Global Optimality ◽  
Worst Case ◽  
Probabilistic Uncertainty ◽  
Structural Design Optimization

Robust structural design optimization with non-probabilistic uncertainties is often formulated as a two-level optimization problem. The top level optimization problem is simply to minimize a specified objective function while the optimized solution at the second level solution is within bounds. The second level optimization problem is to find the worst case design under non-probabilistic uncertainty. Although the second level optimization problem is a non-convex problem, the global optimal solution must be assured in order to guarantee the solution robustness at the first level. In this paper, a new approach is proposed to solve the robust structural optimization problems with non-probabilistic uncertainties. The WCDO problems at the second level are solved directly by the monotonocity analysis and the global optimality is assured. Then, the robust structural optimization problem is reduced to a single level problem and can be easily solved by any gradient based method. To illustrate the proposed approach, truss examples with non-probabilistic uncertainties on stiffness and loading are presented.

scholarly journals Greenfly Aphid Swarm Optimization Algorithm

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Hanan A.R. Akkar ◽  
Sameem Abbas Salman
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Optimization Technique ◽  
Design Problems ◽  
Swarm Optimization ◽  
Engineering Design Problems ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Swarm Intelligence Optimization ◽  
Practical Impact

A new metaheuristic swarm intelligence optimization technique, called general greenfly aphid swarm optimization algorithm, which is proposed by enhancing the performance of swarm optimization through cockroach swarm optimization algorithm. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization algorithm, cockroach swarm optimization and grasshopper optimization algorithm. Numerical experiments show that the greenfly aphid swarm optimization algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblau’s optimization problem, are also considered and the proposed greenfly aphid swarm optimization algorithm is shown to be competitive in those applications.

scholarly journals Concurrent design of a lower limb rehabilitation mechanism

Enfoque UTE ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 57-68
Author(s):  
José Saúl Muñoz Reina ◽  
Miguel Gabriel Villarreal Cervantes ◽  
Leonel German Corona Ramirez ◽  
Robero Castro Medina
Keyword(s):  
Structural Design ◽  
Optimization Problem ◽  
Low Cost ◽  
Lower Limbs ◽  
Robotic Systems ◽  
Concurrent Design ◽  
Dimensional Synthesis ◽  
Limb Rehabilitation ◽  
To Receive ◽  
Lower Limb Rehabilitation

The rehabilitation given by robotic systems is a choice for minimizing the recovery time of a patient and boost their muscular and skeletal capacity on a limb damaged. However, the high cost of these systems limits patients to receive these kind of treatments. The systems of one degree of freedom are a low cost alternative to health care and rehab at home. In this paper, the structural design of an 8-link mechanism for the rehabilitation of lower limbs is performed, based on the approach and solution of an optimization problem in which certain objectives are met, such as dimensional synthesis, and the minimizing of torque to make control easier.

A new hybrid particle swarm optimization approach for structural design optimization in the automotive industry

2012 ◽  
Vol 226 (10) ◽  
pp. 1340-1351 ◽  
Author(s):  
Ali R Yildiz
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Automotive Industry ◽  
Structural Design ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Hybrid Particle Swarm Optimization ◽  
Structural Design Optimization

This paper presents an innovative optimization approach to solve structural design optimization problems in the automotive industry. The new approach is based on Taguchi’s robust design approach and particle swarm optimization algorithm. The proposed approach is applied to the structural design optimization of a vehicle part to illustrate how the present approach can be applied for solving design optimization problems. The results show the ability of the proposed approach to find better optimal solutions for structural design optimization problems.

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