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.
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].