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** 1. Particle group algorithm **

also known as particle swarm optimization algorithm ( PAR __ ti CLE SW ARM OPTI mi zation), abbreviated as PSO, a new evolutionary algorithm that has developed in recent years ((Evolu2tionary Algorithm – EA). The pso algorithm is one of the evolutionary algorithm, and the genetic algorithm , it is also from random solution, looking for the best solution by iteration, it also evaluates the quality of the solution by adaptation However, it is more simple than genetic algorithms, which does not have the crossover and muto operations of the genetic algorithm. It is easy to find the overall best. This algorithm is easy to achieve The advantages of high precision, fast convergence, etc. have caused emphasis on academia, and showing its superiority in solving practical problems. __

** II, genetic algorithm **

< P> Genetic algorithm is a kind of computational mathematics to solve the optimization, an evolutionary algorithm. The evolutionary algorithm initially developed from some phenomena in evolutionary biology, including genetic, mutation, natural choice And hybridization, etc. The genetic algorithm usually implements a simulation. For a most optimized problem, a certain number of candidate (called individual) populations (called chromosome) are more democked. Traditionally, The decisions are denoted (ie 0 and 1 skewers), but can also be used in other representations. Evolution starts from a full random individual population, and then generation generation occurs. In each generation, the adaption of the entire population is evaluated, from the current population A plurality of individuals are selected in randomly (based on their adaptation), producing a new life population by natural selection and mutation, which becomes the current population in the next iteration of the algorithm.

** three , Greedy algorithm **

concept: greedy algorithm is a method that does not pursue the best solution, only hope to get a more satisfactory solution.

greedy algorithm can generally be satisfied Solution, because it saves a lot of time that must be expensive for finding the best solving, the greedy algorithm is often based on the current situation, regardless of various possible overall situations. For example, usa When finding money, in order to make the number of coins retrieved, all of the various issues of changing the change of the change, but start from the biggest currency, consider the currency in the order of decreasing, first try to use a large-faced value Currency, when it is not enough money to consider the next smaller face value. This is the use of greedy algorithms. This method is always the best, because the bank issued by the bank Category and coin face value. If only face values ??are 1, 5 and 11 units of coins, and I hope to retrieve a coin that is 15 units. According to greedgings, you should find 1 11 unit value of coins and 4 1 unit faces of coins, find 5 coins. But the optimal solution is a coin of 3 unit faces.

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