• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.105-112
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• 2015

Generally, the optimal solution of assignment problem has been obtained by Hungarian algorithm with O($n^3$) time complexity. This paper proposes more simple algorithm with O($n^2$) time complexity than Hungarian algorithm. The proposed algorithm simply selects minimum cost in each row, and classified into set S, H, and T. Then, the minimum cost is moved from S to T and $S{\rightarrow}H$, $H{\rightarrow}T$. The proposed algorithm can be obtain the same optimal solution as well-known algorithms and improve the optimal solution of partial unbalanced assignment problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.1-16
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• 1998

The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.115-130
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• 1995

This paper considers a single machine nonpreemptive scheduling problem with a given common due date. In the problem, the optimal job sequence is sought to minimize the sum of earliness/tardiness and flow time measures in the situation where all jobs are available at time zero, and weights per unit length of earliness/tardiness and flow time are V and W, respectively. Some dominant solution properties are characterized to deriva both an optimal starting time for an arbitrary sequence and sequence improvement rules. The optimal schedule is found to the case W .geq. V/. By the way, it is difficult to find the optimal schedule for the case W < V. Therefore, the derived properties are put on together to construct a heuristic solution algorithm for the case W < V, and its effectiveness is rated at the mean relative error of about 3% on randomly generated numerical problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.93-100
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• 1998

The researches of Linear Programming are Khachiyan Method, which uses Ellipsoid Method, and Karmarkar, Affine, Path-Following and Interior Point Method which have Polynomial-Time complexity. In this study, Karmarkar Method is more quickly solved as 50 times then Simplex Method for optimal solution. but some special problem is not solved by Karmarkar Method. As a result, the algorithm by APL Language is proved time efficiency and optimal solution in the Primal-Dual interior point algorithm. Furthermore Karmarkar Method and Primal-Dual interior point Method is compared in some examples.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.293-298
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• 1993

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.565-568
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• 1996

In this paper, a solution method is proposed to calculate the optimum solution to discrete optimal H$_{.inf}$ control problem for feedback of linear time-invariant system states and disturbance variable. From the results of this study, condition of existence and uniqueness of its solution is that transfer matrix of controlled variable to input variable is left invertible and has no invariant zeros on the unit circle of the z-domain as well as extra geometric conditions given in this paper. Through a numerical example, the noniterative solution method proposed in this paper is illustrated.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.301-303
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• 2005

This paper presents long-term shunt capacitor planning using optimal power flow. OPF allows the planning engineer to find feasible solution with minimal amount of engineering time. We used OPF for Shunt capacitor planning to get an optimal solution. The result of OPF is compared to the analysis by the conventional loadflow method and it is proved that OPF gives more cheaper and better planning solution. With the result, we analyzed the operational perspective for the reactive power supply and demand.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.77-83
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• 2015

This paper suggests heuristic algorithm to obtain optimal solution of minimum number of delay aircraft in airport arrivals/departures problem. This problem can be solved only mathematical optimization method. The proposed algorithm selects the minimum delays capacity in various airport capacities for number of arrivals/departures aircraft in $i^{th}$ time interval (15 minutes). In details, we apply median selection method and left-right selection method. This algorithm can be get the optimal solution of minimum number of delay aircraft for sixes actual experimental data.

• Journal of Distribution Science
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• v.15 no.2
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• pp.15-20
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• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.