memetic algorithm


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memetic algorithm

(algorithm)
A genetic algorithm or evolutionary algorithm which includes a non-genetic local search to improve genotypes. The term comes from the Richard Dawkin's term "meme".

One big difference between memes and genes is that memes are processed and possibly improved by the people that hold them - something that cannot happen to genes. It is this advantage that the memetic algorithm has over simple genetic or evolutionary algorithms.

These algorithms are useful in solving complex problems, such as the "Travelling Salesman Problem," which involves finding the shortest path through a large number of nodes, or in creating artificial life to test evolutionary theories.

Memetic algorithms are one kind of metaheuristic.

UNLP memetic algorithms home page.
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References in periodicals archive ?
A Memetic Algorithm (MA) [82] for solving linear equations systems is proposed in paper [67].
In order to address NP-hardness, numerous researchers have worked with various population-based search algorithms such as Monte Carlo [23-25], genetic algorithm [19,26-30], evolutionary programming [31], ant colony optimization [32-34], immune algorithm [35], constraint based chain growth algorithm [36], and hybrid of local search and evolutionary algorithms commonly called memetic algorithm [37-41].
The proposed approach employed an adaptive memetic algorithm to select the best hill climber.
[15] suggest a memetic algorithm based on organizational maps for dynamic scenarios.
Tofighi, "Optimization of quantum-inspired neural network using memetic algorithm for function approximation and chaotic time series prediction," Neurocomputing, vol.
[18] designed a Memetic Algorithm (MA) which introduced a local search process to improve the performance of EA.
The second runner-up was Yuyan Sun, Yuxuan Liang, Zizhen Zhang, and Jiahai Wang, for their paper M-NSGA-II: A Memetic Algorithm for Vehicle Routing Problem with Route Balancing.
Yeh [7] created a memetic algorithm to solve this problem.
"Hybrid Memetic Algorithm With TwoDimensional Discrete Haar Wavelet Transform for Optimal Sensor Placement." IEEE Sensors Journal, 17(7): 2267-2278.
A flexible integrated forward/reverse logistics model with random path-based memetic algorithm. Iranian Journal of Management Studies, 8(2), 287.
[38] put forward a memetic algorithm based on local search chains, named MA-SW-CHAINS, which assigned local search intensity to each individual depending on its features by changing different local search applications.
Cengiz and Tokat have used GA, memetic algorithm (MA) and tabu search (TS) to optimize three different LAA [10].