• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1870-1873
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• 2004

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.290-293
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• 2000

Knowledge discovery refers to the overall process of discovering useful knowledge from data. The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the DSS area. However, they rely on the strict assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the GPS algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.91-107
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• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.85-97
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• 2003

An indefinite stochastic linear-quadratic(LQ) optimal control problem with cross term over an infinite time horizon is studied, allowing the weighting matrices to be indefinite. A systematic approach to the problem based on semidefinite programming (SDP) and .elated duality analysis is developed. Several implication relations among the SDP complementary duality, the existence of the solution to the generalized Riccati equation and the optimality of LQ problem are discussed. Based on these relations, a numerical procedure that provides a thorough treatment of the LQ problem via primal-dual SDP is given: it identifies a stabilizing optimal feedback control or determines the problem has no optimal solution. An example is provided to illustrate the results obtained.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.524-524
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• 2000

We have been developing a method to build one-step-ahead prediction models for time series using genetic programming (GP). Our model building method consists of two stages. In the first stage, functional forms of the models are inherited from their parent models through crossover operation of GP. In the second stage, the parameters of the newborn model arc optimized based on an iterative method just like the back propagation. The proposed method has been applied to various kinds of time series problems. An application to the seismic ground motion was presented in the KACC'99, and since then the method has been improved in many aspects, for example, additions of new node functions, improvements of the node functions, and new exploitations of many kinds of mutation operators. The new ideas and trials enhance the ability to generate effective and complicated models and reduce CPU time. Today, we will present a couple of financial applications, espc:cially focusing on gold price prediction in Tokyo market.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.414-424
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• 2008

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts or components over a given planning horizon. This paper considers the two-level disassembly structure that describes a direct relationship between the used product and its parts or components. To formulate the problem mathematically, we first suggest an integer programming model, and then reformulate it to a dynamic programming model after characterizing properties of optimal solutions. Based on the dynamic programming model, we develop a polynomial exact algorithm and illustrate it with an example problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.18
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• pp.7-15
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• 1988

This study is concerned with selecting mutually dependent quality improvement alternatives with resource constraints. These qualify improvement alternatives art different fro the tradition at alternatives which are independent from each other. In other words, selection of any improvement alternative requires other related specific improvement. Also the overall product quality in a multi stage manufacturing process is characterized by a complex multiplication method rather than a simple addition method which dose not allow to solve a linear knapsack problem despite its popularity in the traditional study. This study suggests a non-linear integer programming model for selecting mutually dependent quality improvement alternatives in multi-stage manufacturing process. In order to apply the model to selecting alternatives. This study also suggests a heuristic mode1 based on a dynamic programming model which is more practical than the non-linear integer programming model. The logic of the heuristic model enables 1) to estimate improvement effectiveness values on all improvement alternatives specifically defined for this study. 2) to arrange the effectiveness values in a descending order, and 3) to select the best one among the alternatives based on their forward and backward linkage relationships. This process repeats to selects other best alternatives within the resource constraints. This process is presented in a Computer programming in Appendix A. Alsc a numerical example of model application is presented in Chapter 4.

• Management Science and Financial Engineering
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• v.7 no.1
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• pp.41-56
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• 2001

This linear fractional - quadratic bilevel programming problem, in which the leader's objective function is a linear fractional function and the follower's objective function is a quadratic function, is studied in this paper. The leader's and the follower's variables are related by linear constraints. The derivations of the optimality conditions are based on Kuhn-Tucker conditions and the duality theory. It is also shown that the original linear fractional - quadratic bilevel programming problem can be solved by solving a standard linear fractional program and the optimal solution of the original problem can be achieved at one of the extreme point of a convex polyhedral formed by the new feasible region. The algorithm is illustrated with the help of an example.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.361-374
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• 2008

Recently, satellite formation flying has been a topic of significant research interest in aerospace society because it provides potential benefits compared to a large spacecraft. Some techniques have been proposed to design optimal formation trajectories minimizing fuel consumption in the process of formation configuration or reconfiguration. In this study, a method is introduced to build fuel-optimal trajectories minimizing a cost function that combines the total fuel consumption of all satellites and assignment of fuel consumption rate for each satellite. This approach is based on collocation and nonlinear programming to solve constraints for collision avoidance and the final configuration. New constraints of nonlinear equality or inequality are derived for final configuration, and nonlinear inequality constraints are established for collision avoidance. The final configuration constraints are that three or more satellites should form a projected circular orbit and make an equilateral polygon in the horizontal plane. Example scenarios, including these constraints and the cost function, are simulated by the method to generate optimal trajectories for the formation configuration and reconfiguration of multiple satellites.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.166-171
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• 2015

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.