Abstract
Design optimization in engineering tends to be very challenging, partly due to the complexity and high nonlinearity of the problem of interest and partly due to stringent design codes in engineering. Conventional algorithms are not the best tools for highly nonlinear global optimization, as they are local search algorithms and thus often miss the global optimality. In addition, design solutions have to be robust and subject to uncertainty in the parameters and tolerance of available components and materials. Metaheuristic algorithms have become increasingly popular in the last two decades. This chapter reviews some of the latest metaheuristics.
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