Optimization of Helical Spring Weight using Meta-heuristic Algorithms
Abstract
Optimization is the act of obtaining the best results under given circumstances. A mathematical theory of optimization is highly in use and is being applied to design where design function can be expressed mathematically. Many techniques like Linear Programming, Branch & Bound technique, Dynamic Programming methods are available to solve optimization problems. But these conventional Methods suffer from certain drawbacks like sticking at suboptimal solution, inefficiency in handling problems having discrete variables etc.To overcome the draw backs of conventional optimization techniques engineers started using non-traditional optimization methods. Particle Swarm Optimization (PSO) and Differential Evolution (DE) come under the category of non-traditional optimization. In this paper PSO and DE are implemented for the weight optimization of helical spring employed in the front suspension system of a passenger car.
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DOI: https://doi.org/10.37591/tmd.v5i2.955
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