We have compared our results with Genetic algorithm to prove the effectiveness of PSO algorithm over genetic algorithm.doi:10.1016/j.procs.2016.03.002Gosain, AnjanaHeenaElsevier B.V.Procedia Computer ScienceA Gosaina, Heena, Materialized Cube Selection using Particle Swarm Optimization algorithm, 7th...
This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the <italic>p</italic>-power transformation and penalty function techni
Compared to the Monge–Kantorovich approach, the Monge-Brenier optimization method can significantly reduce the number of unknown variables from O(n2) to O(n), where n is the number of discretized sample points on the target domain and can solve the optimal transport map via the gradient ...
1. To solve the problem on algorithm New-Apriori,a new algorithm called MWFS algorithm for mining weighted frequent itemsets was proposed. 针对New-Apriori算法的不足之处,提出了一种新的挖掘加权频繁项集的算法——MWFS算法,该算法能有效挖掘出含有权重较大项目的加权频繁项集,其挖掘结果更具有价值。参...
According to the No Free Lunch Theorem15, it is known that there is no single optimization algorithm that can universally solve all problems. Similarly, SSA is not without its drawbacks: in complex problems, it may exhibit a slower rate of optimization in later stages and runs the risk of ...
Thus, Marching Cubes provides a trade-off between quality and speed and performs much faster than any of such optimization methods. The branching problem is not considered explicitly. This, however, is the least problem, since there are hardly any general assumptions to tackle this problem in a...
to surround more territory than the opponent, a famous game in China [53], commanding an artificial robotic hand to solve the Rubik cube [41], outperforming in fault detection and diagnosis [66], spread of Covid-19 forecasting, electric load forecasting, and natural language processing (NLP)...
In the last decade, computer-aided engineering (CAE) tools have become a determinant factor in the analysis of engineering problems. In fact, they bring a clear reduction of time in the design phase of a new product thanks to parametrical studies based o
A lot of researchers are working on developing a perfect metaheuristic algorithm to solve all optimization problems. Unfortunately, it is often found that when an algorithm produces superior results for a certain problem, it usually performs inferiorly for others (Dutta, Bhattacharyya, Dey, & Platos...
In this section, an efficient optimization algorithm is used to solve the above model. To achieve the optimization of the model, we continuously improve the performance of the algorithm by iteratively updating G ( 1 ) , G ( 2 ) , and G ( 3 ) . Specifically, the iterative update formulas...