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Everything about MCACEA
Framework
MCACEA is a general framework that uses a single evolutionary algorithm (EA) per agent sharing their optimal solutions to coordinate the evolutions of the EAs populations using cooperation objectives. This framework can be used to optimize some characteristics of multiple cooperating agents in mathematical optimization problems. More specifically, due to its nature in which both individual and cooperation objectives are optimize, MCACEA is used in multi-objective optimization problems. Wikipedia →
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đź”— Related topics
- Fitness function A fitness function is a particular type of objective or cost function that is used to summarize, as a single figure of merit, how close a given candidate…
- Parallel metaheuristic Parallel metaheuristic is a class of techniques that are capable of reducing both the numerical effort[clarification needed] and the run time of a metaheuristic…
- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
- Cellular evolutionary algorithm A cellular evolutionary algorithm (cEA) is a kind of evolutionary algorithm (EA) in which individuals cannot mate arbitrarily, but every one interacts…
- Memetic algorithm In computer science and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary…
- Genetic algorithm A genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA)…
- Evolutionary multimodal optimization In applied mathematics, multimodal optimization deals with optimization tasks that involve finding all or most of the multiple (at least locally optimal)…
- Genetic operator A genetic operator is an operator used in evolutionary algorithms (EA) to guide the algorithm towards a solution to a given problem. There are three main…