Abstract A large number of problems in engineering, science and management can be formulated as global optimization problem [19, 147]. Unfortunately, global optimization problems are very difficult to solve. In order to understand the difficulties it is important to note that all local optimization techniques can at most locate a local minimum. Moreover, there is no local criterion to decide whether a local solution is also the global solution. Furthermore, locally optimal solutions often prove insufficient for real-world engineering problems [41]. Therefore, conventional optimization methods that make use of derivatives, gradients and the like are, in general, not able to locate or identify the global optimum.


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