• IE interfaces
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• v.7 no.1
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• pp.75-80
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• 1994

In a recent article, Leon et al. lucidly explained the ideas of the Taguchi two-stage procedure for parameter design optimization, and proposed alternative performance measures called PerMIA to the signal-to-noise ratios. On the other hand, Box proposed an empirical approach to the problem based upon monotone transformations of the performance characteristic(y). This paper develops procedures for parameter design optimization under the assumptions that the expected loss(not necessarily a mean squared error loss) is increasing with respect to the variance of the error in y, and that the mean of y satisfies certain conditions of adjustability. It turns out that the variance of the error in y can play the role of PerMIA, and it is further shown that the derived PerMIA can be adapted to the Box empirical procedure for the minimization of the expected loss in the original metric.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.201-208
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• 2010

This research is about developing an efficient solution procedure for the vehicle routing problem under varying vehicle moving speeds for hour-based time interval. Different moving speeds for every hour is too difficult condition to solve for this type of combinatorial optimization problem. A methodology to divide the 12 hour based time interval offered by government into 5 different time intervals and then divide delivery area into 12 small divisions first and then re-organizing them into 5 groups. Then vehicle moving speeds are no longer varying in each of the 5 divisions. Therefore, a typical TSP solution procedure may be applied to find the shortest path for all 5 divisions and then connect the local shortest paths to form a delivery path for whole area. Developed solution procedures are explained in detail with 60 points example.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.121-134
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• 1999

In this paper, I propose a hybrid genetic algorithm(HGAM) incorporating a greedy interchange local optimization procedure for the multiobjective vehicle scheduling problems with service due times where three conflicting objectives of the minimization of total vehicle travel time, total weighted tardiness, and fleet size are explicitly treated. The vehicle is allowed to visit a node exceeding its due time with a penalty, but within the latest allowable time. The HGAM applies a mixed farming and migration strategy in the evolution process. The strategy splits the population into sub-populations, all of them evolving independently, and applys a local optimization procedure periodically to some best entities in sub-populations which are then substituted by the newly improved solutions. A solution of the HCAM is represented by a diploid structure. The HGAM uses a molified PMX operator for crossover and new types of mutation operator. The performance of the HGAM is extensively evaluated using the Solomons test problems. The results show that the HGAM attains better solutions than the BC-saving algorithm, but with a much longer computation time.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.182-188
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• 2008

Automated parking systems, which automatically park and retrieve vehicles, have been steadily replacing conventional parking systems. The spiral parking system is a type of automated parking systems that has cylindrical parking tower. We develop an economic design model of spiral parking system based on a recursive optimization and simulation procedure in which the dynamic nature of the parking system can be integrated into the mathematical programming model. The optimal values of design parameters are found that gives the minimum total cost while complying with the desired performance of the system.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.14-35
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• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.13-35
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• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Korean Journal of Optics and Photonics
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• v.8 no.2
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• pp.88-94
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• 1997

Photographic lenses and an aspheric optical pickup-lens are designed by using damped least-squares(DLS) method. We start optimization with arbitrary initial damping factor. To improve the rate of convergence and the stability in optimization, we apply the special procedure that estimates numerical adequacy of derivative increments of variables to the DLS method. When the initial damping factor is almost equal to the median of series of eigenvalues, the convergence and the stability of the method significantly are improved. Optimized lenses have the performance of each target.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.1
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• pp.44-50
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• 2015

This paper presents a heuristic process-optimization procedure for minimizing warpage in injection-molded parts based on the dynamic robust design methodology. The injection molding process is known to have intrinsic variations of its process conditions due to various factors, including incomplete process control facilities. The aim of the robust design methodology advocated by Taguchi is to determine the optimum design variables in a system which is robust to variations in uncontrollable factors. The proposed procedure can determine the optimal robust conditions of injection molding processes at a minimum cost through a trade-off strategy between the degree of warpage and the packing time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.866-870
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• 2010

This paper presents a application of Harmony Search (HS) algorithm for optimal placement of distributed generations(DGs) in distribution systems. In optimization procedure, the HS algorithm denotes the searching ability for the global optimal solution with simple coding of the iteration procedure, and shows the fast convergence characteristics for getting solutions. The HS algorithm is tested on 9 buses and 69 buses distribution systems, and the results prove its effectiveness to determine appropriate placement points of DGs and reducing amount of active power without the occurrence of any mis-determination in selection of its capacity.