Such problems cannot be handled by classical methods (e.g., gradient methods) that only compute local optima. Perhaps, the traditional techniques have a variety of drawbacks paving the way for advent of new and versatile methodologies to solve such optimization problems. However, there are some difficulties with most of the traditional methods of optimization and these are given below.Ī large body of literature is available on traditional methods for solving the above problems.
In direct search method, only the function value is necessary, whereas the gradient based methods require gradient information to determine the search direction. Some of them are direct search methods and others are gradient methods. There are several methods available in the literature of optimization. Thus, optimization techniques can effectively be used to ensure optimal production rate. While designing machine elements, optimization helps in a number of ways to reduce material cost, to ensure better service of components, to increase production rate, and many such other parameters. It plays a vital role in machine design because the mechanical components are to be designed in an optimal manner. Optimization is a method of obtaining the best result under the given circumstances. The objective function may have many local optima, whereas the designer is interested in the global optimum or a reasonable and acceptable optimum. In real time optimization (design) problems, the number of design variables will be very large, and their influence on the objective function to be optimized can be very complicated (nonconvex), with a nonlinear character. Perhaps these traditional optimization procedures perform well in many practical cases they may fail to perform in more complex design situations. Analytical or numerical methods for calculating the extremes of a function have long been applied to engineering computations. For example, in a centrifugal pump, the optimization of the impeller is computationally and mathematically simpler than the optimization of the complete pump. Hence, it is a general procedure to apply optimization techniques for individual components or intermediate assemblies rather than a complete assembly or system. However, design optimization for a complete mechanical system leads to a cumbersome objective function with a large number of design variables and complex constraints. Majority of mechanical design includes an optimization task in which engineers always consider certain objectives such as weight, wear, strength, deflection, corrosion, and volume depending on the requirements. optimized weight of a belt-pulley drive under some constraints using geometric programming. Reddy to optimize weight of a hollow shaft after satisfying a few constraints. The problem of volume minimization of a closed coil helical spring was solved using some traditional technique under some constraints.
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