What Is Simulated Annealing?

Simulated Anneal (SA) is a general-purpose probability algorithm used to find the optimal solution to a proposition in a large search space. Simulated annealing was invented by S. Kirkpatrick, CDGelatt, and MPVecchi in 1983. V.ern & yacute; also independently invented the algorithm in 1985. The simulated annealing algorithm is one of the effective methods to solve the TSP problem.

The principle of simulated annealing is also similar to that of metal annealing:

State space and state generation functions

1) Search space is also called

The generation and acceptance of the new solution of the simulated annealing algorithm can be divided into the following four steps:

The first step is to generate a location function

step1: Download the commonly used scikit-opt on GitHub ^[3]

The simulated annealing algorithm is widely used and can be solved

(1) Design a suitable state generation function so that it displays the full-space dispersion or local regionality of the state according to the needs of the search process;
(2) Designing efficient annealing strategies;
(3) Avoid roundabout search of status;
(4) using a parallel search structure;
(5) In order to avoid falling into local minimum, improve the control method of temperature;
(6) Select a suitable initial state;
(7) Design appropriate algorithm termination criteria. ^[5]