更改

===避开障碍Barrier avoidance===

===避障Barrier avoidance===

When choosing the candidate generator {{code|neighbour()}} one must also try to reduce the number of "deep" local minima—states (or sets of connected states) that have much lower energy than all its neighbouring states. Such "closed [[drainage basin|catchment]] basins" of the energy function may trap the simulated annealing algorithm with high probability (roughly proportional to the number of states in the basin) and for a very long time (roughly exponential on the energy difference between the surrounding states and the bottom of the basin).

When choosing the candidate generator {{code|neighbour()}} one must also try to reduce the number of "deep" local minima—states (or sets of connected states) that have much lower energy than all its neighbouring states. Such "closed [[drainage basin|catchment]] basins" of the energy function may trap the simulated annealing algorithm with high probability (roughly proportional to the number of states in the basin) and for a very long time (roughly exponential on the energy difference between the surrounding states and the bottom of the basin).

为此，我们将<code>s</code>和<code>e</code> </code> 设置为<code>sbest</code>和<code>ebest</code>并可能重新启动退火时刻表。重新启动的决定可能基于几个标准。其中值得注意的有:基于固定步数的重启，基于当前能量是否高于目前获得的最佳能量，随机重启等。

为此，我们将<code>s</code>和<code>e</code> </code> 设置为<code>sbest</code>和<code>ebest</code>并可能重新启动退火时刻表。重新启动的决定可能基于几个标准。其中值得注意的有:基于固定步数的重启，基于当前能量是否高于目前获得的最佳能量，随机重启等。

==Related methods==

==相关算法  Related methods==

* [[Metropolis–Hastings algorithm|Interacting Metropolis–Hasting algorithms]] (a.k.a. [[Particle filter|Sequential Monte Carlo]]<ref name=":3">{{Cite journal|title = Sequential Monte Carlo samplers - P. Del Moral - A. Doucet - A. Jasra - 2006 - Journal of the Royal Statistical Society: Series B (Statistical Methodology) - Wiley Online Library| doi=10.1111/j.1467-9868.2006.00553.x|volume=68| issue=3|journal=Journal of the Royal Statistical Society, Series B|pages=411–436|arxiv=cond-mat/0212648|year = 2006|last1 = Del Moral|first1 = Pierre| last2=Doucet| first2=Arnaud| last3=Jasra| first3=Ajay}}</ref>) combined simulated annealing moves with an acceptance-rejection of the best fitted individuals equipped with an interacting recycling mechanism.

* [[Metropolis–Hastings algorithm|Interacting Metropolis–Hasting algorithms]] (a.k.a. [[Particle filter|Sequential Monte Carlo]]<ref name=":3">{{Cite journal|title = Sequential Monte Carlo samplers - P. Del Moral - A. Doucet - A. Jasra - 2006 - Journal of the Royal Statistical Society: Series B (Statistical Methodology) - Wiley Online Library| doi=10.1111/j.1467-9868.2006.00553.x|volume=68| issue=3|journal=Journal of the Royal Statistical Society, Series B|pages=411–436|arxiv=cond-mat/0212648|year = 2006|last1 = Del Moral|first1 = Pierre| last2=Doucet| first2=Arnaud| last3=Jasra| first3=Ajay}}</ref>) combined simulated annealing moves with an acceptance-rejection of the best fitted individuals equipped with an interacting recycling mechanism.

==Further reading==

==进一步阅读 Further reading==

*A. Das and B. K. Chakrabarti (Eds.), ''[ftp://nozdr.ru/biblio/kolxoz/M/MP/Das%20A.,%20Chakrabarti%20B.K.%20(eds.)%20Quantum%20Annealing%20and%20Related%20Optimization%20Methods%20(LNP0679,%20Springer,%202005)(384s)_MP_.pdf Quantum Annealing and Related Optimization Methods],'' Lecture Note in Physics, Vol. 679, Springer, Heidelberg (2005)

*A. Das and B. K. Chakrabarti (Eds.), ''[ftp://nozdr.ru/biblio/kolxoz/M/MP/Das%20A.,%20Chakrabarti%20B.K.%20(eds.)%20Quantum%20Annealing%20and%20Related%20Optimization%20Methods%20(LNP0679,%20Springer,%202005)(384s)_MP_.pdf Quantum Annealing and Related Optimization Methods],'' Lecture Note in Physics, Vol. 679, Springer, Heidelberg (2005)

*模拟退火的自我指导课程维基学院项目。

*模拟退火的自我指导课程维基学院项目。

*谷歌在叠加使用、不使用量子计算机的Ars技术中讨论了谷歌所使用的D波计算机可能实际上是一个高效的模拟退火协处理器的可能性。

*谷歌在叠加使用、不使用量子计算机的Ars技术中讨论了谷歌所使用的D波计算机可能实际上是一个高效的模拟退火协处理器的可能性。

{{Major subfields of optimization}}

{{Major subfields of optimization}}