• Journal of Korean Institute of Industrial Engineers
• /
• v.26 no.2
• /
• pp.117-127
• /
• 2000

In this paper, we propose a new convex combination weight rule for the cross decomposition method which is known to be one of the most reliable and promising strategies for the large scale optimization problems. It is called generalized cross decomposition, a modification of linear mean value cross decomposition for specially structured linear programming problems. This scheme puts more weights on the recent subproblem solutions other than the average. With this strategy, we are having more room for selecting convex combination weights depending on the problem structure and the convergence behavior, and then, we may choose a rule for either faster convergence for getting quick bounds or more accurate solution. Also, we can improve the slow end-tail behavior by using some combined rules. Also, we provide some computational test results that show the superiority of this strategy to the mean value cross decomposition in computational time and the quality of bounds.

• Journal of Korean Institute of Industrial Engineers
• /
• v.37 no.2
• /
• pp.124-131
• /
• 2011

In this research report, we propose a heuristic algorithm with some primal recovery strategies for capacitated facility location problems (CFLP), which is a well-known combinatorial optimization problem with applications in distribution, transportation and production planning. Many algorithms employ the branch-and-bound technique in order to solve the CFLP. There are also some different approaches which can recover primal solutions while exploiting the primal and dual structure simultaneously. One of them is a MVCD (Mean Value Cross Decomposition) ensuring convergence without solving a master problem. The MVCD was designed to handle LP-problems, but it was applied in mixed integer problems. However the MVCD has been applied to only uncapacitated facility location problems (UFLP), because it was very difficult to obtain "Integrality" property of Lagrangian dual subproblems sustaining the feasibility to primal problems. We present some heuristic strategies to recover primal feasible integer solutions, handling the accumulated primal solutions of the dual subproblem, which are used as input to the primal subproblem in the mean value cross decomposition technique, without requiring solutions to a master problem. Computational results for a set of various problem instances are reported.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.9 no.2
• /
• pp.3-8
• /
• 1984

This paper considers the intermediate warehouse location problem in a two stage distribution system where commodities are delivered from the given set of capacitated factories to customers via uncapacitated intermediate warehouses. In order to determine the subset of warehouses to open which minimizes the total distribution costs including the fixed costs associated with opening warehouses, the cross decomposition method for mixed integer programming recently developed by T.J. Van Roy is used. The cross decomposition unifies Benders decomposition and Lagrangean relaxation into a single framework that involves successive solutions to a primal subproblem and a dual subproblem. In our problem model, primal subproblem turns out to be a transshipment problem and dual subproblem turns out to be an intermediate warehouse location problem with uncapacitated factories.

• Nuclear Engineering and Technology
• /
• v.49 no.5
• /
• pp.1006-1009
• /
• 2017

We discuss the problems of scattering in this framework, and show that the applied method is very useful in the investigation of the effect of the resonance in the observed scattering cross sections. In this study, not only the scattering cross sections but also the decomposition of the scattering cross sections was computed for the ${\alpha}-{\alpha}$ system. To obtain the decomposition of scattering cross sections into resonance and residual continuum terms, the complex scaled orthogonality condition model and the extended completeness relation are used. Applying the present method to the ${\alpha}-{\alpha}$ and ${\alpha}-n$ systems, we obtained good reproduction of the observed phase shifts and cross sections. The decomposition into resonance and continuum terms makes clear that resonance contributions are dominant but continuum terms and their interference are not negligible. To understand the behavior of observed phase shifts and the shape of the cross sections, both resonance and continuum terms are calculated.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.15 no.1
• /
• pp.23-35
• /
• 1990

A mathematical model for a dynamic capacitate facility location problem is formulated by a mixed integer problem. The objective of the model is to minimize total discounted costs that include fixed charges and distributed costs. The Cross Decomposition method of Van Roy is extended and applied to solve the dynamic capacitated facility location problem. The method unifies Benders Decomposition and Lagrangean relaxation into a single framework. It successively solves a transportation problem and a dynamic uncapacitated facility location problem as two subproblems. Computational results are compared with those of general mixed integer programming.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.7 no.6
• /
• pp.979-994
• /
• 2015

The mode shapes of a segmented hull model towed in a model basin were predicted using both the Proper Orthogonal Decomposition (POD) and cross random decrement technique. The proper orthogonal decomposition, which is also known as Karhunen-Loeve decomposition, is an emerging technology as a useful signal processing technique in structural dynamics. The technique is based on the fact that the eigenvectors of a spatial coherence matrix become the mode shapes of the system under free and randomly excited forced vibration conditions. Taking advantage of the simplicity of POD, efforts have been made to reveal the mode shapes of vibrating flexible hull under random wave excitation. First, the segmented hull model of a 400 K ore carrier with 3 flexible connections was towed in a model basin under different sea states and the time histories of the vertical bending moment at three different locations were measured. The measured response time histories were processed using the proper orthogonal decomposition, eventually to obtain both the first and second vertical vibration modes of the flexible hull. A comparison of the obtained mode shapes with those obtained using the cross random decrement technique showed excellent correspondence between the two results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.810-831
• /
• 2019

Recently, continuous dimensional emotion recognition from audiovisual clues has attracted increasing attention in both theory and in practice. The large amount of data involved in the recognition processing decreases the efficiency of most bimodal information fusion algorithms. A novel algorithm, namely the incomplete Cholesky decomposition based kernel cross factor analysis (ICDKCFA), is presented and employed for continuous dimensional audiovisual emotion recognition, in this paper. After the ICDKCFA feature transformation, two basic fusion strategies, namely feature-level fusion and decision-level fusion, are explored to combine the transformed visual and audio features for emotion recognition. Finally, extensive experiments are conducted to evaluate the ICDKCFA approach on the AVEC 2016 Multimodal Affect Recognition Sub-Challenge dataset. The experimental results show that the ICDKCFA method has a higher speed than the original kernel cross factor analysis with the comparable performance. Moreover, the ICDKCFA method achieves a better performance than other common information fusion methods, such as the Canonical correlation analysis, kernel canonical correlation analysis and cross-modal factor analysis based fusion methods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.2
• /
• pp.246-251
• /
• 2013

In this paper, we consider the stability of linear systems without delay decomposition. A less conservative result obtained without delay decomposition is strongly required since it is a basis to get an improved result by applying simple delay decomposition. Unlike the most popular Lyapunov-Krasovski(L-K) function, we consider the cross terms between variables. Based on this new structure of L-K function, we derive a delay-dependent stability criterion in the form of linear matrix inequality(LMI). Finally, we show, by well-known two examples, that our result is less conservative than the recent results.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.07a
• /
• pp.389-390
• /
• 2019

Tensor decomposition, proven to be an efficient data processing method, can be used to provide data-driven services. we propose a novel datadriven mutation strategy for parent individuals selection, namely tensor-based DE with parapatric and cross-generation(TPCDE).

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1999.04a
• /
• pp.316-317
• /
• 1999