摘要近几年来，智能优化算法在许许多多的领域之中得到了巨大的发展和广泛的应用，虽然算法的在收敛性方面，智能优化算法已经获得了一定的研究成果，但是也有其不足的地方需要进一步研究，那就是智能优化算法后面并没有强大而坚实的理论基础作为支撑。这篇文章将围绕以下几个方面进行研究：62369

一、依据“摸石头过河”的想法来源，提出摸石头过河算法[1]，这种算法是一种效率较高、速度较快的随机优化算法。摸石头过河算法的思想是以一个解为搜索的开始，并向此解的附近进行搜索另外的解，以此类推。用这个算法对几个常常被学者们用来测试的经典的测试函数进行测试，测试结果表明，这个算法能够相当大的提高其收敛速度和精度。

二、对算法的优化进行研究。优化技术这方面的内容包含了对优化问题和优化算法的思考和解决，其中，找出优化解的特征的这一类问题被称之为优化问题，而怎样来找出优化解的这一类问题被称之为优化算法，也就是解决优化问题的方法步骤。之后会对几个经典的智能优化算法进行研究并且与摸石头过河算法进行一些对比。

三、依据算法的优化技术，对摸石头过河算法进行一些优化，从而提高该算法的计算效果和收敛速度。优化过后同意会用几个测试函数进行测试，通过数据说明该算法的优势。

四、采用几种算法对几个经典的测试函数进行测试，以直观的感受和数据的说服力给人展示算法的收敛速度和精度。

毕业论文关键字：随机优化算法；摸石头过河算法；连续空间优化；智能优化算法

Abstract In recent years, intelligent optimization algorithm among many areas has been tremendous development and wide application, although the algorithm in terms of convergence, intelligent optimization algorithm has gained some achievements, but also has its inadequacies of the further research is needed, it is not intelligent optimization algorithm back strong and solid theoretical foundation as a support. This article will focus on the following research areas:

First, according to "touch stones" source of ideas put forward to Wading across Stream Algorithm [1], this algorithm is a high efficiency, faster stochastic optimization algorithms. Wading across Stream Algorithm is thought to start searching for a solution, and to search for another solution near this solution, and so on. With this algorithm, several scholars have often been used to test classic test function test, the test results show that this algorithm can considerably improve the convergence speed and accuracy.

Second, the optimization algorithm to study. Content optimization technology in this area includes the optimization problems and optimization algorithms to think and solve, where to find the solutions of optimization features of this kind of problem is called optimization, and this class how to find the optimal solution problem is called optimization, that is, to solve the optimization problem of method steps. After a few classics have intelligent optimization algorithm to study and Wading across Stream Algorithm and make some comparison algorithm.

Third, according to the algorithm optimization technology to Wading across Stream Algorithm some optimization algorithm to improve the algorithm to calculate the effectiveness and speed of convergence. After optimization consent will be tested with several test functions, the data illustrate the advantages of the algorithm.

Fourth, the use of several algorithms for several classic test functions for testing to give an intuitive feel and convincing data to show the convergence speed and accuracy.

Keywords: random optimization algorithm; Wading across Stream Algorithm; continuous space optimization; Intelligent optimization algorithm