2017 | OriginalPaper | Chapter
18. Cyclical Parthenogenesis Optimization Algorithm
Abstract
Over the last few decades, metaheuristic algorithms have been successfully used for solving complex global optimization problems in science and engineering. These methods, which are usually inspired by natural phenomena, do not require any gradient information of the involved functions and are generally independent of the quality of the starting points. As a result, metaheuristic optimizers are favorable choices when dealing with discontinuous, multimodal, non-smooth, and non-convex functions, especially when near-global optimum solutions are sought, and the intended computational effort is limited.
