Tiago G. Goto, Hossein Rostami Najafabadi, Guilherme C. Duran, E. K. Ueda, A. K. Sato, Thiago de C. Martins, R. Y. Takimoto, H. Gohari, A. Barari, M. Tsuzuki
{"title":"结晶启发式模拟退火的通用性:在大量问题中的应用","authors":"Tiago G. Goto, Hossein Rostami Najafabadi, Guilherme C. Duran, E. K. Ueda, A. K. Sato, Thiago de C. Martins, R. Y. Takimoto, H. Gohari, A. Barari, M. Tsuzuki","doi":"10.5772/INTECHOPEN.98562","DOIUrl":null,"url":null,"abstract":"This chapter is related to several aspects of optimization problems in engineering. Engineers usually mathematically model a problem and create a function that must be minimized, like cost, required time, wasted material, etc. Eventually, the function must be maximized. This function has different names in the literature: objective function, cost function, etc. We will refer to it in the chapter as objective function. There is a wide range of possibilities for the problems and they can be classified in different ways. At first, the values of the parameters can be continuous, discrete (integers), cyclic (angles), intervals, and combinatorial. The result of the objective function can be continuous, discrete (integers) or intervals. One very difficult class of problems have continuous parameters and discrete objective function, this type of objective function has very weak sensibility. This chapter shows the versatility of the simulated annealing showing that it can have different possibilities of parameters and objective functions.","PeriodicalId":340860,"journal":{"name":"Optimization Problems in Engineering [Working Title]","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Versatility of Simulated Annealing with Crystallization Heuristic: Its Application to a Great Assortment of Problems\",\"authors\":\"Tiago G. Goto, Hossein Rostami Najafabadi, Guilherme C. Duran, E. K. Ueda, A. K. Sato, Thiago de C. Martins, R. Y. Takimoto, H. Gohari, A. Barari, M. Tsuzuki\",\"doi\":\"10.5772/INTECHOPEN.98562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This chapter is related to several aspects of optimization problems in engineering. Engineers usually mathematically model a problem and create a function that must be minimized, like cost, required time, wasted material, etc. Eventually, the function must be maximized. This function has different names in the literature: objective function, cost function, etc. We will refer to it in the chapter as objective function. There is a wide range of possibilities for the problems and they can be classified in different ways. At first, the values of the parameters can be continuous, discrete (integers), cyclic (angles), intervals, and combinatorial. The result of the objective function can be continuous, discrete (integers) or intervals. One very difficult class of problems have continuous parameters and discrete objective function, this type of objective function has very weak sensibility. This chapter shows the versatility of the simulated annealing showing that it can have different possibilities of parameters and objective functions.\",\"PeriodicalId\":340860,\"journal\":{\"name\":\"Optimization Problems in Engineering [Working Title]\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optimization Problems in Engineering [Working Title]\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5772/INTECHOPEN.98562\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optimization Problems in Engineering [Working Title]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.98562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Versatility of Simulated Annealing with Crystallization Heuristic: Its Application to a Great Assortment of Problems
This chapter is related to several aspects of optimization problems in engineering. Engineers usually mathematically model a problem and create a function that must be minimized, like cost, required time, wasted material, etc. Eventually, the function must be maximized. This function has different names in the literature: objective function, cost function, etc. We will refer to it in the chapter as objective function. There is a wide range of possibilities for the problems and they can be classified in different ways. At first, the values of the parameters can be continuous, discrete (integers), cyclic (angles), intervals, and combinatorial. The result of the objective function can be continuous, discrete (integers) or intervals. One very difficult class of problems have continuous parameters and discrete objective function, this type of objective function has very weak sensibility. This chapter shows the versatility of the simulated annealing showing that it can have different possibilities of parameters and objective functions.