been implemented in nearly all optimization fields, including computational intelligence, design, and planning applications. However, many researchers still propose a large number of variants to improve the performance of the PSO algorithm. In order to improve the diversity accuracy and avoid the low l...
The whale optimization algorithm has received much attention since its introduction due to its outstanding performance. However, like other algorithms, the whale optimization algorithm still suffers from some classical problems. To address the issues of
Question 1: Power Allocation in Wireless Communication System Based on Water-Filling AlgorithmConsider a broadcast communication system in which a central base station (BS) transmits signals to \bm{…
In general, deterministic optimization algorithms are unidirectional, i.e., there exists at most one way to proceed (otherwise, the algorithm gets terminated), and do not use random numbers in any step of execution. On the other hand, in stochastic optimization problems or optimization under ...
2.8 Adam优化算法(Adam optimization algorithm) Adam(Adaptive Moment Estimation)就是将Momentum和RMSprop结合在一起, 2.9 学习率衰减(Learning rate decay) 学习率为固定值时梯度下降最后会在最小值附近摆动,不会精确收敛; 随时间慢慢减少学习率,可以缩小曲线在最小值附近的摆动范围; ...
The integration of optimization algorithms into power systems has been discussed in several textbooks, but this is the first to include the integration methods and the developed codes. As such, it is a useful resource for undergraduate and graduate students, researchers and engineers trying to solve...
and we quantify the error in performance introduced by running the algorithm on a sample drawn from an unknown query distribution.We investigate the problem of finding optimized support association rules for a single numerical attribute, where the optimized region is a union of k disjoint intervals ...
With respect to complexity and solution methods, linear programming is a polynomial problem, well solved, in theory and in practice, through the simplex algorithm or interior points methods. Mixed-integer linear programming, on the other hand, is an NP-hard problem, which does not make it ...
One of the most famous metaheuristic MOO methods that is widely used for multiobjective optimization of energy systems is the nondominated sorting genetic algorithm known as NSGA-II. In this algorithm, solutions are categorized based on the Pareto concept and sorting nondominated solutions into non...