{"title":"用并行遗传算法求解密码问题","authors":"Reza Abbasian, M. Mazloom","doi":"10.1109/ICCEE.2009.25","DOIUrl":null,"url":null,"abstract":"Cryptarithmetic is a class of constraint satisfaction problems which includes making mathematical relations between meaningful words using simple arithmetic operators like ‘plus’ in a way that the result is conceptually true, and assigning digits to the letters of these words and generating numbers in order to make correct arithmetic operations as well. A simple way to solve such problems is by depth first search (DFS) algorithm which has a big search space even for quite small problems. In this paper we proposed a solution to this problem with genetic algorithm and then optimized it by using parallelism. We also showed that the algorithm reaches a solution faster and in a smaller number of iterations than similar algorithms.","PeriodicalId":343870,"journal":{"name":"2009 Second International Conference on Computer and Electrical Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Solving Cryptarithmetic Problems Using Parallel Genetic Algorithm\",\"authors\":\"Reza Abbasian, M. Mazloom\",\"doi\":\"10.1109/ICCEE.2009.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cryptarithmetic is a class of constraint satisfaction problems which includes making mathematical relations between meaningful words using simple arithmetic operators like ‘plus’ in a way that the result is conceptually true, and assigning digits to the letters of these words and generating numbers in order to make correct arithmetic operations as well. A simple way to solve such problems is by depth first search (DFS) algorithm which has a big search space even for quite small problems. In this paper we proposed a solution to this problem with genetic algorithm and then optimized it by using parallelism. We also showed that the algorithm reaches a solution faster and in a smaller number of iterations than similar algorithms.\",\"PeriodicalId\":343870,\"journal\":{\"name\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEE.2009.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Conference on Computer and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEE.2009.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
摘要
密码学是一类约束满足问题,它包括使用简单的算术运算符,如“加号”,在有意义的单词之间建立数学关系,使结果在概念上是正确的,并为这些单词的字母分配数字,并生成数字,以便进行正确的算术运算。解决这类问题的一种简单方法是采用深度优先搜索(deep first search, DFS)算法,该算法即使对于相当小的问题也有很大的搜索空间。本文提出了用遗传算法解决该问题的方法,并利用并行性对其进行了优化。我们还表明,该算法比类似的算法更快,迭代次数更少。
Solving Cryptarithmetic Problems Using Parallel Genetic Algorithm
Cryptarithmetic is a class of constraint satisfaction problems which includes making mathematical relations between meaningful words using simple arithmetic operators like ‘plus’ in a way that the result is conceptually true, and assigning digits to the letters of these words and generating numbers in order to make correct arithmetic operations as well. A simple way to solve such problems is by depth first search (DFS) algorithm which has a big search space even for quite small problems. In this paper we proposed a solution to this problem with genetic algorithm and then optimized it by using parallelism. We also showed that the algorithm reaches a solution faster and in a smaller number of iterations than similar algorithms.