scholarly journals A Cross Entropy Algorithm for Classification with $\delta$−Patterns

2006 ◽  
Vol DMTCS Proceedings vol. AG,... (Proceedings) ◽  
Author(s):  
Gabriela Alexe ◽  
Gyan Bhanot ◽  
Adriana Climescu-Haulica
Keyword(s):  
Optimization Problem ◽  
Genomic Data ◽  
Maximal Clique ◽  
Large Datasets ◽  
Entropy Method ◽  
Combinatorial Optimization Problem ◽  
Cross Entropy ◽  
Cross Entropy Method ◽  
International Audience ◽  
Generation Problem

International audience A classification strategy based on $\delta$-patterns is developed via a combinatorial optimization problem related with the maximal clique generation problem on a graph. The proposed solution uses the cross entropy method and has the advantage to be particularly suitable for large datasets. This study is tailored for the particularities of the genomic data.

A Cross-Entropy Method for Solving Passenger Flow Routing Problem

2013 ◽  
Vol 756-759 ◽  
pp. 3617-3621 ◽  
Author(s):  
Yang Jiang ◽  
Xing Chen Zhang ◽  
Tian Tian Gan
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Entropy Method ◽  
Combinatorial Optimization Problem ◽  
Cross Entropy ◽  
Flow Routing ◽  
Passenger Flow ◽  
Cross Entropy Method ◽  
Routing Design ◽  
The Cross

In this paper, a new design optimization method-cross entropy methods for passenger flow routing in passenger hubs is employed, in order to develop rational and efficient passenger flow routing program, which will help improving the passenger flow organization. According to the description and characteristics of the problem, we transform the problem into a combinatorial optimization problem, so that it is convenient to explore the best solution. The numerical example declares that the method given above can obtain the optimal solution under the condition of fixed demand. Results show that the cross entropy method is effective, and can be well applied in passenger flow routing design problem. Systematic studying the passenger terminal passenger flow routing design optimization techniques and methods and developing rational and efficient passenger flow routing program will help improving the organization of passenger flow. According to the description of the problem and the characteristics of itself, the paper transforms the problem into a combinatorial optimization problem, so that it is convenient to explore the best solution. The paper also employs the cross entropy method to solve the problems. Numerical example declares that the method given above can obtain the optimal solution under the condition of fixed demand. Results show that the cross entropy method is effective, and this method can be well applied in passenger flow routing design problem.

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