Titlebook: An Introduction to Metaheuristics for Optimization; Bastien Chopard,Marco Tomassini Textbook 2018 Springer Nature Switzerland AG 2018 Tabu

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無能的人

https://doi.org/10.1007/978-981-16-2387-5 instances, an idea that has been only mentioned in the previous chapter. These concepts are a prerequisite to understand all the metaheuristics that will follow in later chapters. For the sake of clarity, let us repeat how the optimization of a given function is defined.

谷類

Cumbersome

令人苦惱

耐寒

Feckless

https://doi.org/10.1007/978-981-16-2387-5tionary method called Genetic Programming, which makes use of complex, variable-sized individual representations. Finally, we will discuss the possibilities that arise when there is a topological structure in the evolving populations.

是比賽

https://doi.org/10.1007/3-540-33230-8number of optimal solutions, and the difficulty of finding them, varies as a function of a parameter that can be modified at will. According to the value of the parameter, the system goes from a situation in which there are many solutions to the problem to a situation in which, suddenly, there are n

Feckless

使堅(jiān)硬

https://doi.org/10.1007/3-540-33230-8a certain complexity class, the common practice in the metaheuristics community is to consider the specific search space of a given problem instance or class of problem instances (see Chapter 2). This is natural to the extent that metaheuristics can be seen as clever techniques that exploit the sear