Genetic Algorithms with Memory- and Elitism-Based Immigrants in Dynamic Environments
نویسندگان
چکیده
منابع مشابه
Genetic Algorithms with Memory- and Elitism-Based Immigrants in Dynamic Environments
In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new enviro...
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Addressing dynamic optimization problems has been a challenging task for the genetic algorithm community. Over the years, several approaches have been developed into genetic algorithms to enhance their performance in dynamic environments. One major approach is to maintain the diversity of the population, e.g., via random immigrants. This paper proposes an elitism-based immigrants scheme for gen...
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Many of the problems considered in optimization and learning assume that solutions exist in a dynamic. Hence, algorithms are required that dynamically adapt with the problem’s conditions and search new conditions. Mostly, utilization of information from the past allows to quickly adapting changes after. This is the idea underlining the use of memory in this field, what involves key design issue...
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Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution(s) of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interes...
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ژورنال
عنوان ژورنال: Evolutionary Computation
سال: 2008
ISSN: 1063-6560,1530-9304
DOI: 10.1162/evco.2008.16.3.385