Estimating optimal stopping rules in the multiple best choice problem with minimal summarized rank via the cross-entropy method

Authors:
T. V. Polushina
Affiliations:
Department of Physics and Mathematics, Mari State University, Yoshkar-Ola, Russia
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

Citing 3
Cited 1

The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)

The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)
A genetic algorithm for facility layout problems of different manufacturing environments

Computers and Industrial Engineering
Solving Facility Layout Problem Using an Improved Genetic Algorithm

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

Multi-criteria service selection with optimal stopping in dynamic service-oriented systems

ICDCIT'10 Proceedings of the 6th international conference on Distributed Computing and Internet Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

The best choice problem is an important class of the theory of optimal stopping rules. In this article, we present the Cross-Entropy method for solving the multiple best choice problem with the minimal expected ranks of selected objects. Computational results showed that the Cross-Entropy method is producing high-quality solution.