• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.75-82
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• 2015

Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.

• Korean Journal of Computational Design and Engineering
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• v.14 no.3
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• pp.207-216
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• 2009

Modern engineering design problems involve complexity of disciplinary coupling and difficulty of problem formulation. Multidisciplinary design optimization can overcome the complexity and design optimization software or frameworks can lessen the difficulty. Recently, a growing number of new multidisciplinary design optimization techniques have been proposed. However, each technique has its own pros and cons and it is hard to predict a priori which technique is more efficient than others for a specific problem. In this study, a software system has been developed to directly solve MDO problems with minimal input required. Since the system is based on MATLAB, it can exploit the optimization toolbox which is already developed and proven to be effective and robust. The framework is devised to change an MDO technique to another as the optimization goes on and it is called a reconfigurable MDO framework. Several numerical examples are shown to prove the validity of the reconfiguration idea and its effectiveness.

• Structural Engineering and Mechanics
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• v.33 no.3
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• pp.285-306
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• 2009

In the literature the problem of the topology optimization of the structure is usually solved for one, clearly described from the mechanical point of view material. Generally the topology optimization answers the question of the distribution of this mentioned above material within the design domain. Finally, material-voids distribution it is obtained. In this paper, for the structure mainly strengthened or sometimes weakened by the inclusions, the variation approach of the topology optimization problem is formulated. This multi material approach may be useful for the design process of various mechanical or civil engineering structures which need to be more "refined" and more "optimal" than they can be using previous topology optimization procedures of optimization one material structures.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.161-167
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• 2000

In this paper, we propose a design method for BAMs(bidirectiona1 associative memories) which can perform the function of bidirectional association efficiently. Based on the theoretical investigation about the properties of BAMs, we first formulate the problem of finding a BAM that can store the given pattern pairs as stable states with high error correction ratio in the form of a constrained optimization problem. Next, we transform the constrained optimization problem into a GEVP(genera1ized eigenvalue problem), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.30-35
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• 2013

Motivated by the emergency scheduling in a transportation network, this paper considers a transportation problem, in which, the truck times and transportation costs are assumed as uncertain variables. To meet the demand in the practical applications, two optimization objectives are considered, one is the total costs and another is the completion times. And then, a multi-objective optimization model is developed according to the situation in applications. Because there are commensurability and conflicting between the two objectives commonly, a solution does not necessarily exist that is best with respective to the two objectives. Therefore, the problem is reduced to a single objective model, which is an uncertain programming with a chance-constrain. After some analysis, its equivalent deterministic form is obtained, which is a nonlinear programming. Based on a stepwise optimization strategy, a solution method is developed to solve the problem. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.327-333
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• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1636-1648
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• 2006

In this paper, we propose a new optimization approach to the rate control problem in a wired-cum-wireless network. A primal-dual interior-point(PDIP) algorithm is used to find the solution of the rate optimization problem. We show a comparison between the dual-based(DB) algorithm and PDIP algorithm for solving the rate control problem in the wired-cum-wireless network. The PDIP algorithm performs much better than the DB algorithm. The PDIP can be considered as an attractive method to solve the rate control problem in network. We also present a numerical example and simulation to illustrate our conclusions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.113-116
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• 1995

In this study, we formulate production costing problem with environmental and operational constraints into an optimization problem of LP form. In the process of formulation, auxiliary constraints on which reflect unit loading order are constructed to reduce the size of optimization problem by economic operation rules. As a solution of the optimization problem in LP form, we use Karmarkar's method which performs much faster than simplex method in solving large scale LP problem. The proposed production costing algorithm is applied to IEEE Reliability Test System, and performs production simulation under environmental and operational constraints. Test and computer results are given to show the accuracy and usefulness of the proposed algorithm in the field of power system planning.