Automated production cutting optimization for minimizing material waste of pipelines in prefabricated MEP systems based on integer programming. [PDF]
Fan X, Yang L, Zhao X.
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Density clustering based fast and stable satellite selection for LEO navigation. [PDF]
Lu Z, Zhang S, Wang Y, Xiong J, Zhao R.
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Architectures, Protocols and Algorithms of Sensor Networks-Second Edition. [PDF]
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A novel hybrid metaheuristic algorithm and response surface methodology approach for predictive modeling and optimization of cementitious compressive strength. [PDF]
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Trajectory Tracking Control for Subsea Mining Vehicles Based on Fuzzy PID Optimised by Genetic Algorithms. [PDF]
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A genetic algorithm with disruptive selection
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1996Genetic algorithms are a class of adaptive search techniques based on the principles of population genetics. The metaphor underlying genetic algorithms is that of natural evolution. Applying the "survival-of-the-fittest" principle, traditional genetic algorithms allocate more trials to above-average schemata.
Ting Kuo, Shu-Yuen Hwang
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Sexual Selection for Genetic Algorithms
Artificial Intelligence Review, 2003Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling ...
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