• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.899-902
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• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.1
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• pp.1-11
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• 2000

In this paper, optimum design problem of R.C. continuous beam is considered and GUI system is developed for using at the practical design. Objective function lot formulation of optimum design problem is made up of the costs of concrete, reinforcing steel and formwork. Design variables are width, effective depth of the beam and steel ratio and design constraints are considered on the strength, serviceability, durability and geometrical conditions. The optimum design problem is solved by using sequential linear programming(SLP), sequential convex programming(SCP) and compared their effectiveness. Also this paper shows the application at practical design work according to the development of GUI system using visual basic.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.1
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• pp.103-108
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• 2012

In this paper, the optimal design of a spring-type gravity compensation system for an articulated robot is presented. Sequential quadratic programming (SQP) is adopted to resolve various nonlinear constraints in spring design such as stress, buckling, and fatigue constraints, and to reduce computation time. In addition, continuous relaxation method is used to explain the integer-valued design variables. The simulation results show that the gravity compensation system designed by proposed method improves the performance effectively without additional weight gain in the main workspace.

• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.70-76
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• 1999

In this paper, a mixed-integer programming approach is presented for adjusting the voltage profiles in a power system. The advent of large-scaled system makes the reactive power and voltage problem-an attempt to achieve an overall improvement of system security, service quality and economy-more complex and seriously, Although the problem is originally a nonlinear optimization problem, it can be formulated as a mixed integer linear programming(MILP) problem without deteriorating of solution accuracy to a certain extent. The MILP code is developed by the branch and bound process search for the optimal solution. The variable for modeling transformer tap positions is handled as discrete one, and other variables continuous ones. Numerical data resulting from case study using a modified IEEE 30 bus system with outaged line show that the MILP can produce more reductions of magnitude in the operating cost. The convergence characteristics of the results are also presented and discussed.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.391-399
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• 2006

In order to solve the optimization problem of designing the trajectory of three-dimensional horizontal well, we establish a multi-phase, nonlinear, stochastic dynamic system of the trajectory of horizontal well. We take the precision of hitting target and the total length of the trajectory as the performance index. By the integration of the state equation, this model can be transformed into a nonlinear stochastic programming. We discuss here the necessary conditions under which a local solution exists and depends in a continuous way on the parameter (perturbation). According to the properties we propose a revised Hooke-Jeeves algorithm and work out corresponding software to calculate the local solution of the nonlinear stochastic programming and the expectancy of the performance index. The numerical results illustrate the validity of the proposed model and algorithm.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.383-390
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• 2011

Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.7
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• pp.484-489
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• 1988

Sufficient conditions concerning the perturbation region of system parameters, which guarantee the asymptotic stability of linear time- varying systems, are presented. These conditions are obtained by Lyapunov function approach for continuous-time and discrete-time systems. Also, a computational algorithm using nonlinear programming is proposed for finding the maximum perturbation region which satisfies the sufficient condition for the continuous-time systems. The technique of finding the solution for the continuous-time systems can also be applied to the discrete-time systems. In the continuous-time case, it is shown by an example that the method proposed in this paper yields much larger perturbation region of parameters than other previously reported results. An example of the perturbation region of system paramters for the discrete-time system is also given.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.2
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• pp.15-20
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• 2015

This paper introduces a new airspace design method for continuous climb operation (CCO). The optimization problem is formulated as Mixed-Integer Linear Program (MILP) to maximize the upper limits of altitude on the waypoints to facilitate continuous climb for aircraft. In the proposed method, the interactions with other flight procedures are considered as well as various aircraft flight performances. The proposed method is applied to one of the departure procedures of Incheon International Airport (ICN) to demonstrate its performances.

• Journal of the Chungcheong Mathematical Society
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• v.23 no.3
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• pp.435-442
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• 2010

This paper is concerned with algorithm for calculating one-sided best simultaneous approximation, in the case of continuous functions. we will apply any subgradient algorithm. In other words, we consider the algotithms from a mathematical, rather then computational, point of view.

• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.373-382
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• 1995

The weighting strategy has received a great attention and has been widely applied to multicriterion optimization. This gaper examines a global criterion method (GCM) with the weighting objectives strategy in fuzzy structural engineering problems. Fuzziness of those problems are in their design goals, constraints and variables. Most of the constraints are originated from analysis of engineering mechanics. The GCM is verified to be equivalent to fuzzy goal programming via a truss design. Continued and mixed discrete variable spaces are presented and examined using a fuzzy global criterion method (FGCM). In the design process a weighting parameter with fuzzy information is introduced into the design and decision making. We use a uniform machine-tool spindle as an illustrative example in continuous design space. Fuzzy multicriterion optimization in mixed design space is illustrated by the design of mechanical spring stacks. Results show that weighting strategy in FGCM can generate both the best compromise solution and a set of Pareto solutions in fuzzy environment. Weighting technique with fuzziness provides a more relaxed design domain, which increases the satisfying degree of a compromise solution or improves the final design.