{"title":"企鹅抱团优化","authors":"M. M. al-Rifaie","doi":"10.4018/ijats.2014040101","DOIUrl":null,"url":null,"abstract":"In our everyday life, we deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multiagent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic – Penguin Huddling Optimisation or PHO – whose inspiration is beckoned from the huddling behaviour of emperor penguins in Antarctica. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour and the derivation of the optimal value for its single adjustable parameter in the update equation. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms.","PeriodicalId":93648,"journal":{"name":"International journal of agent technologies and systems","volume":"8 1","pages":"1-29"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Penguins Huddling Optimisation\",\"authors\":\"M. M. al-Rifaie\",\"doi\":\"10.4018/ijats.2014040101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In our everyday life, we deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multiagent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic – Penguin Huddling Optimisation or PHO – whose inspiration is beckoned from the huddling behaviour of emperor penguins in Antarctica. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour and the derivation of the optimal value for its single adjustable parameter in the update equation. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms.\",\"PeriodicalId\":93648,\"journal\":{\"name\":\"International journal of agent technologies and systems\",\"volume\":\"8 1\",\"pages\":\"1-29\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of agent technologies and systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijats.2014040101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of agent technologies and systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijats.2014040101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In our everyday life, we deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multiagent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic – Penguin Huddling Optimisation or PHO – whose inspiration is beckoned from the huddling behaviour of emperor penguins in Antarctica. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour and the derivation of the optimal value for its single adjustable parameter in the update equation. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms.