Titlebook: Recent Progress in Data Engineering and Internet Technology; Volume 1 Ford Lumban Gaol Conference proceedings 2013 Springer-Verlag GmbH Ber

Wernickes-area

1876-1100 database technologies, ?intelligent information systems, data engineering applications, ?internet security, internet data management, web search, data grids, cloud computing, web-based application, and other r978-3-642-44797-6978-3-642-28807-4Series ISSN 1876-1100 Series E-ISSN 1876-1119

憲法沒(méi)有

歡笑

auxiliary

Wu Di,Hou Jiuyang,Li Qiang offline genetic algorithm-based hyper-heuristic method for tuning a set of problems. The offline hyper-heuristic procedure is applied to 26 benchmark test problems. The obtained MOEA/D implementations are compared with six decomposition-based EMO algorithms. The experimental results show that the t

Cubicle

Keedong Yoo Pareto solutions for each population and the ensuing multi-criterion decision-making complexities make the MOCoEv research and application be challenging. This paper should spur immediate further attention to multi-objective co-evolutionary problem solving studies.

生銹

Chunjiao Dong,Chunfu Shao,Dan Zhao,Yinhong Liu offline genetic algorithm-based hyper-heuristic method for tuning a set of problems. The offline hyper-heuristic procedure is applied to 26 benchmark test problems. The obtained MOEA/D implementations are compared with six decomposition-based EMO algorithms. The experimental results show that the t

寄生蟲(chóng)

Lidong Fu,Lin Gaore constructed to learn the implicit graph representation on nodes and edges. The network outputs are then converted into the probability distribution of the Pareto set, from which a set of non-dominated solutions can be sampled non-autoregressively. Experimental results on MO-FLP instances of diffe

蜈蚣

Behrouz Safarinejadiangnificance of the proposed approach to a number of popular engineering design problems. Searching for a set of solutions with regularity-based principles for different platforms is a practically important task. This paper should encourage more similar algorithmic developments in the near future.

馬籠頭

absolve