Nadir Siddig, Zhang Ze Qiang, Abdallah Mokhtar, Ahmed Abualnor
{"title":"混合鲸鱼群算法优化拆解线平衡问题","authors":"Nadir Siddig, Zhang Ze Qiang, Abdallah Mokhtar, Ahmed Abualnor","doi":"10.54388/jkues.v2i3.204","DOIUrl":null,"url":null,"abstract":"The disassembly of waste products positively affects the environment, reduces the risk of environmental pollution, reduces the risk of spreading dangerous parts to the life of living entities, and provides the continuity of life on this planet.This research aims to contribute to the aforementioned of maintaining a clean environment by developing algorithms that help solve the problems of dismantling waste products and polluting the environment. In previous literature, researchers developed algorithms for artificial fish, improved artificial fish, and artificial whales to search for solutions with higher evidence instead From the local evidence, in this paper the artificial fish algorithm has been hybridized with the artificial whale algorithm for the purpose of developing solutions, and this method depends on the artificial fish flock first searching for food and here representing global solutions and avoiding predating traps (hooks with trap food), and after finding a flock The artificial swarm is the real food. The artificial whale sends bubbles to collect the swarm of artificial fish in the place of global high solutions, and gets them at once. The proposed algorithm was compared with the algorithms in the previous literature, and the results were as follows:Workstation was decreased by 0.5\\% to 22.2\\%, idle time was reduced by 82.5\\% to 84.0\\%, the demand index was reduced by 15\\% to 24.2\\%, and the hazardous index was reduced by 1.7\\% to 3.4\\%.","PeriodicalId":129247,"journal":{"name":"Journal of Karary University for Engineering and Science","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid Whale-fish swarm algorithm to optimize disassembly line balancing problem\",\"authors\":\"Nadir Siddig, Zhang Ze Qiang, Abdallah Mokhtar, Ahmed Abualnor\",\"doi\":\"10.54388/jkues.v2i3.204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The disassembly of waste products positively affects the environment, reduces the risk of environmental pollution, reduces the risk of spreading dangerous parts to the life of living entities, and provides the continuity of life on this planet.This research aims to contribute to the aforementioned of maintaining a clean environment by developing algorithms that help solve the problems of dismantling waste products and polluting the environment. In previous literature, researchers developed algorithms for artificial fish, improved artificial fish, and artificial whales to search for solutions with higher evidence instead From the local evidence, in this paper the artificial fish algorithm has been hybridized with the artificial whale algorithm for the purpose of developing solutions, and this method depends on the artificial fish flock first searching for food and here representing global solutions and avoiding predating traps (hooks with trap food), and after finding a flock The artificial swarm is the real food. The artificial whale sends bubbles to collect the swarm of artificial fish in the place of global high solutions, and gets them at once. The proposed algorithm was compared with the algorithms in the previous literature, and the results were as follows:Workstation was decreased by 0.5\\\\% to 22.2\\\\%, idle time was reduced by 82.5\\\\% to 84.0\\\\%, the demand index was reduced by 15\\\\% to 24.2\\\\%, and the hazardous index was reduced by 1.7\\\\% to 3.4\\\\%.\",\"PeriodicalId\":129247,\"journal\":{\"name\":\"Journal of Karary University for Engineering and Science\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Karary University for Engineering and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54388/jkues.v2i3.204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Karary University for Engineering and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54388/jkues.v2i3.204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid Whale-fish swarm algorithm to optimize disassembly line balancing problem
The disassembly of waste products positively affects the environment, reduces the risk of environmental pollution, reduces the risk of spreading dangerous parts to the life of living entities, and provides the continuity of life on this planet.This research aims to contribute to the aforementioned of maintaining a clean environment by developing algorithms that help solve the problems of dismantling waste products and polluting the environment. In previous literature, researchers developed algorithms for artificial fish, improved artificial fish, and artificial whales to search for solutions with higher evidence instead From the local evidence, in this paper the artificial fish algorithm has been hybridized with the artificial whale algorithm for the purpose of developing solutions, and this method depends on the artificial fish flock first searching for food and here representing global solutions and avoiding predating traps (hooks with trap food), and after finding a flock The artificial swarm is the real food. The artificial whale sends bubbles to collect the swarm of artificial fish in the place of global high solutions, and gets them at once. The proposed algorithm was compared with the algorithms in the previous literature, and the results were as follows:Workstation was decreased by 0.5\% to 22.2\%, idle time was reduced by 82.5\% to 84.0\%, the demand index was reduced by 15\% to 24.2\%, and the hazardous index was reduced by 1.7\% to 3.4\%.