• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.60-67
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• 2016

In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.126-132
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• 2008

The bin packing problem (BPP) is an NP-Complete Problem. The problem can be described as there are $N=\{1,2,{\cdots},n\}$ which is a set of item indices and $L=\{s1,s2,{\cdots},sn\}$ be a set of item sizes sj, where $0<sj{\leq}1$, ${\forall}j{\in}N$. The objective is to minimize the number of bins used for packing items in N into a bin such that the total size of items in a bin does not exceed the bin capacity. Assume that the bins have capacity equal to one. In the past, many researchers put on effort to find the heuristic algorithms instead of solving the problem to optimality. Then, the quality of solution may be measured by the asymptotic worst-case ratio or the average-case ratio. The First Fit Decreasing (FFD) is one of the algorithms that its asymptotic worst-case ratio equals to 11/9. Many researchers prove the asymptotic worst-case ratio by using the weighting function and the proof is in a lengthy format. In this study, we found an easier way to prove that the asymptotic worst-case ratio of the First Fit Decreasing (FFD) is not more than 11/9. The proof comes from two ideas which are the occupied space in a bin is more than the size of the item and the occupied space in the optimal solution is less than occupied space in the FFD solution. The occupied space is later called the weighting function. The objective is to determine the maximum occupied space of the heuristics by using integer programming. The maximum value is the key to the asymptotic worst-case ratio.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.1
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• pp.31-38
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• 2008

This paper deals with the nonlinear optimal control approach to helicopter maneuver problems using the indirect method. We apply a penalty function to the integral deviation from a prescribed trajectory to convert the system optimality to an unconstrained optimal control problem. The resultant two-point boundary value problem has been solved by using a multiple-shooting method. This paper focuses on the model selection strategies to resolve the problem of numerical instability and high wait time when a high fidelity model with rotor dynamics is applied. Four different types of helicopter models are identified, two of which are linear models with or without rotor models, as well as two models which include the nonlinear mathematical model for rotor in its formulation. The relative computation time and the number of function calls for each model are compared in order to provide a guideline for the selection of helicopter model.

• Journal of Korean Association for Spatial Structures
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• v.7 no.4
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• pp.89-96
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• 2007

The fundamental frequency maximization of beam structures is carried out by using strain energy based topology optimization technique. It mainly uses the modal strain energy distributions induced by the mode shapes of the structures. The modal strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. The resizing algorithm devised from the optimality criteria method is used to update the hole size of the cell existing in each finite element. The beams with three different boundary conditions are used to investigate the optimum topologies against natural mode shapes. From numerical test, it is found to be that the optimum topologies of the beams produced by the adopted technique have hugh increases in some values of natural frequencies and especially the technique is very effective to maximize the fundamental frequency of the structures.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.130-140
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• 2011

This paper proposes an optimal posture for the task-oriented movement of dual arm manipulator. A stability criterion function which consists of three kinds of feature-representative parameters has been utilized to define the optimal posture. The first parameter is the force which is applied to the object. The torque of each joint and position of arm are attained from the current sensor and encoder, respectively. From these two data, the applied force to an object is estimated using sum of vectors of the joint torques estimated from the measured current. In order to investigate the robustness of each posture, the variation of the end-effector from the encoder information has been utilized as the second parameter. And for the last parameter for the optimality, the total energy consumption has been used. The total consuming energy of each posture can be computed from the current information and the battery voltage. The proposed robot structure consists of a mobile inverted pendulum and dual manipulators. In order to define the optimal posture for the each object, external disturbances are applied to the mobile inverted pendulum robot and the first and second parameters are investigated to find the optimal posture among the pre-selected most representative postures. Finally, the proposed optimal posture has been verified by the proposed stability criterion function which consists of total force to the object, the fluctuation of the end-effector position, and total energy consumption. The effectiveness of the proposed algorithms has been verified and demonstrated through the practical simulations and real experiments.

• Journal of Korean Association for Spatial Structures
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• v.5 no.3 s.17
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• pp.83-89
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• 2005

This paper provides the results of the investigation on the optimum topology of simply supported deep beam structures with multi-point load cases. In this study, the strain energy to be minimized is considered as the objective function and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. In this study, the sensitivities of topology optimization parameters to the optimum topology of the deep bean structures is investigated and also the effect of filtering process on the optimum topology is thoroughly tested. From numerical tests, the optimum topology of the deep beam is closely related with the optimization parameters used in the iteration and the filtering process play important role in order to find the optimum topology of the deep beam.

• Journal of Korean Association for Spatial Structures
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• v.7 no.5
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• pp.67-74
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• 2007

The unsymmetrically layered artificial material model is consistently introduced to find the optimum topologies of the plate structures. Reissner-Mindlin (RM) plate theory is adopted to formulate the present 9-node plate element considering the first-order shear deformation of the plates. In the topology optimization process, the strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. In addition, the resizing algorithm based on the optimality criteria is used to update the hole size introduced in the proposed artificial material model. Several numerical examples are rallied out to investigate the performance of the proposed technique. From numerical results, the proposed topology optimization techniques are found to be very effective to produce the optimum topology of plate structures. In particular, the proposed unsymmetric stiffening layer model make it possible to produce more realistic stiffener design of the plate structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.1
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• pp.1-8
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• 2014

Using the level set and the meshfree methods, we develop a topological shape optimization method applied to linear elasticity problems. Design gradients are computed using an efficient adjoint design sensitivity analysis(DSA) method. The boundaries are represented by an implicit moving boundary(IMB) embedded in the level set function obtainable from the "Hamilton-Jacobi type" equation with the "Up-wind scheme". Then, using the implicit function, explicit boundaries are generated to obtain the response and sensitivity of the structures. Global nodal shape function derived on a basis of the reproducing kernel(RK) method is employed to discretize the displacement field in the governing continuum equation. Thus, the material points can be located everywhere in the continuum domain, which enables to generate the explicit boundaries and leads to a precise design result. The developed method defines a Lagrangian functional for the constrained optimization. It minimizes the compliance, satisfying the constraint of allowable volume through the variations of boundary. During the optimization, the velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition for the Lagrangian functional. Compared with the conventional shape optimization method, the developed one can easily represent the topological shape variations.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.400-411
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• 2011

Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components-process variables experiments depend on the mixture components-process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. In this paper we propose three starting models for the mixture components-process variables experiments. One of the starting model we are considering is the model which includes product terms up to cubic order interactions between mixture effects and the linear & pure quadratic effect of the process variables from the product model. In this paper, we propose a method for finding robust designs and practical designs with respect to D-, G-, and I-optimality for the various starting combined models and then, we find practically efficient and robust designs for estimating the regression coefficients for those models. We find the prediction capability of those recommended designs in the case of three components and three process variables to be good by checking FDS(Fraction of Design Space) plots.