• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.277-280
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• 2004

In the research of biomechanical engineering, robotics and neurophysiology, to clarify the mechanism of human bipedal walking is of major interest. It serves as a basis of developing several applications such as rehabilitation tools and humanoid robots Nevertheless, because of complexity of the neuronal system that Interacts with the body dynamics system to make walking movements, much is left unknown about the details of locomotion mechanism. Researchers were looking for the optimal model of the neuronal system by trials and errors. In this paper, we applied Genetic Programming to induce the model of the nervous system automatically and showed its effectiveness by simulating a human bipedal walking with the obtained model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2350-2364
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• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.55-76
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• 1997

This paper presents a heuristic solution for the three dimensional container loading problem with boxes which are different in size. The container loading problem is formulated as a zero-one mixed integer programming model whose objective is to maximize the container utilization. Due to its problem complexity, we propose a heuristic based on layered loading technique. Also, presented is a way to achieve the weighting balance of the stacked boxes. A micro-computer based program is developed which generates container loading pattern provided by the proposed heuristic. The results are displayed by computer-graphic. To evaluate the performance of the proposed heuristic, computational experiments are performed. The results indicate that in most of the cases the proposed heuristic performs better than an existing heuristic in terms of the container utilization.

• Journal of Information Technology Services
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• v.3 no.2
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• pp.99-104
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• 2004

Conventional and public-key cryptography has been widely accepted as a base technology for the design of computer security systems. D-classes have the potential for application to conventional and public-key cryptography. However, there are very few results on D-classes because the computational complexity of D-class computation is NP-complete. This paper discusses the design of algorithms for the efficient computation of D-classes and the Java implementation of them. In addition, the paper implements the same D-class computation algorithms in C and shows the performance of C and Java programming languages for the computation-intensive applications by comparing their execution results.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.937-940
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• 1988

The problem of minimization of energy, consumed by the robot manipulator, is important, notably for larger manipulators, higher working speeds, and loads. Obviously, the stated problem requires the application of optimal control theory, which is being successfully applied for linear system and certain classes of nonlinear systems. However, the application of optimal control theory(in energy or time optimization) leads to substantial practical difficulties, so that significant simplifications are usually performed, either in model complexity or by neglecting the existing constraints. In this paper the problem of obtaining such an optimization method. which would take into account the complete system dynamics and all the constraints is considered. The only method found to be suitable for such a complex optimization should be based on dynamic programming.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.101-106
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• 2015

This paper suggests heuristic algorithm with polynomial time complexity for rigging elections problem that can be obtain the optimal solution using linear programming. The proposed algorithm transforms the given problem into adjacency graph. Then, we divide vertices V into two set W and D. The set W contains majority distinct and the set D contains minority area. This algorithm applies divide-and-conquer method that the minority area D is include into majority distinct W. While this algorithm using simple rule, that can be obtains the optimal solution equal to linear programing for experimental data. This paper shows polynomial time solution finding rule potential in rigging elections problem.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.97-103
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• 2016

This paper deals with the cycle time minimization problem that determines the productivity in printed circuit board (PCB) with n components using the m placement machines. This is known as production cycle time determination problem (PCTDP). The polynomial time algorithm to be obtain the optimal solution has been unknown yet, therefore this hard problem classified by NP-complete. This paper gets the initial assignment result with the machine has minimum unit placement time per each component firstly. Then, the balancing process with reallocation from overhead machine to underhead machine. Finally, we perform the swap optimization and get the optimal solution of cycle time $T^*$ within O(mn) computational complexity. For experimental data, the proposed algorithm can be obtain the same result as integer programming+branch-and-bound (IP+B&B) and B&B.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.734-741
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• 2002

The importance of efficient Supply Chain Management is increasing in accordance with recent industrial environment, such as globalization of business, complexity and diversity of company's management structure, and variety of customer's demand. In a rapidly changed environment of business, quick and efficient decision making is the important matter to the survival of the company. The purpose of this study supports decision making for efficient supply chain management. In this study, we consider simultaneously and mutually reflecting the preference of each constituent (Supplier, Manufacturing plant, Distribution center, Customer) on supply chain network, and decide company's strategic choice and coordinated production/distribution models of company. The Analytical Hierarchy Process is used for decision making of qualitative and quantitative elements. We use the results of AHP as inputs and propose mathematical models thru Mixed Integer Programming.

• Korean Management Science Review
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• v.10 no.1
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• pp.193-205
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• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.3-11
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• 1993

We propose a new dual simplex method using a primal interior point. The dropping variable is chosen by utilizing the primal feasible interior point. For a given dual feasible basis, its corresponding primal infeasible basic vector and the interior point are used for obtaining a decreasing primal feasible point The computation time of moving on interior point in our method takes much less than that od Karmarker-type interior methods. Since any polynomial time interior methods can be applied to our method we conjectured that a slight modification of our method can give a polynomial time complexity.