• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.93-96
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• 2003

The generalized knapsack problem, or gknap is the combinatorial optimization problem of optimizing a nonnegative linear functional over the integral hull of the intersection of a polynomially separable 0 - 1 polytope and a knapsack constraint. Among many potential applications, the knapsack, the restricted shortest path, and the restricted spanning tree problem are such examples. We establish some necessary and sufficient conditions for a gknap to admit a fully polynomial approximation scheme, or FPTAS, To do so, we recapture the scaling and approximate binary search techniques in the framework of gknap. This also enables us to find a condition that a gknap does not have an FP-TAS. This condition is more general than the strong NP-hardness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.140-147
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• 2012

Vehicle routing problem is one of the traveling salesman problems with various conditions such as vehicle capacity limits, delivery time windows, as well as time dependent speeds in metropolitan area. In this research hourly vehicle moving speeds information in a typical metropolitan area are analyzed to use the results in the design procedure of VRP heuristic. Quality initial vehicle routing solutions can be obtained with adaption of the analysed results of the time periods with no vehicle speed changes. This strategy makes complicated time dependent vehicle speed simple to solve. Time dependent vehicle speeds are too important to ignore to obtain optimum vehicle routing search for real life logistics systems.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.342-344
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• 2002

This paper presents a new strategy to find starting points for placing optimally Phasor Measurement Units(PMUs). The performance of the starting point, initial placement set of PMUs, affect critically the computational burden and/or time, because the Optimal PMU Placement (OPP) problem is formulated the combinatorial optimization. By analyzing the properties of OPP solutions on IEEE sample systems in detail, a new strategy for initial PMU placement, in this paper, is proposed. To verify the performance of the suggested strategy, the comparison with the existing strategy and the new one, on IEEE sample systems. is performed. By using the new strategy, the numbers of search spaces to solve the OPP problem is drastically decreased.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1071-1076
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• 2003

Evolutionary algorithm is recognized as a promising approach to solving multi-objective combinatorial optimization problems. When no preference information of decision makers is given, multi-objective optimization problems have been commonly used to search for diverse and good Pareto optimal solution. In this paper we propose a new multi-objective evolutionary algorithm based on competitive coevolutionary algorithm, and demonstrate the applicability of the algorithm. The proposed algorithm is designed to promote both population diversity and rapidity of convergence. To achieve this, the strategies of fitness evaluation and the operation of the Pareto set are developed. The algorithm is applied to job shop scheduling problems (JSPs). The JSPs have two objectives: minimizing makespan and minimizing earliness or tardiness. The proposed algorithm is compared with existing evolutionary algorithms in terms of solution quality and diversity. The experimental results reveal the effectiveness of our approach.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.303-308
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• 1992

In this study, we propose a shared storage system which is more efficient policy than MIS(Mixed Intermediate Storage) policy for relatively rare storage system and can be called CIS(Common Intermediate Storage) policy. Using this strategy, we develop a new completion time algorithm and apply it to two kinds of optimal or near optimal scheduling method; combinatorial search and simulated annealing method. We also extend this strategy to other storage policy, for example MIS policy, with PLC(Programmable Logic Controller) logic and on/off action of electronic valves. It thus can be accepted as a basic form of FMS(Flexible Manufacturing System) for operating various storage policies. Finally we suggest the interlocking block to compansate for the shortcoming of CIS policy, i.e, complication of operation and safety, resulting in a basic batch process automation mode.

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.1-8
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• 2005

In a metal grating manufacturing process, the cutting operation allocates the gratings and cut them out from given panels or a plate sheets. Before the cutting operation an operator generates a cutting plan. The cutting plan should decide how pieces of metal rectangles i.e., gratings, are allocated and cut from the panel. This plan generation is a deal of weight on the production cost. the generation of cutting plan is similar to the general two-dimensional cutting problem. In this paper, we first define cutting problem and Af algorithm of Artificial Intelligence to solve the problem. Also, through a simulation, we compare the proposed cutting algorithm to an existing method in terms of material loss

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.623-625
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• 1998

This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

• Lingua Humanitatis
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• v.1 no.1
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• pp.295-321
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• 2001

This paper attempts to demonstrate how the linguistic and mythological features of the shamanic language make it incantatory, or ′enchanting′. Passages used in shamanic rites manifest linguistic characteristics that point to their own norms and conventions, as well as some mythological features that contribute to the undecipherablity of the shamanic language. Focusing on the estranged linguistic and mythological features, I propose that shamanic languages can be best interpreted in terms of the linguistic hierarchization, a notion that has been developed since Roman Jakobson′s poetics. The present study adopts Eisele′s framework that reinterprets Jakobsonian hierarchization into a slightly revised notion on the basis of the "degree of combinatorial freedom" and the "degree of semantic immediacy", looking into a set of paradigm examples in search of some parallel structures characterizing the shamanic language. The enchanting effect of this peculiar form of language, it is argued, is due mostly to the frequent use of lexical parallelism, which works in the reverse direction of the normal process of interpretation.

• IE interfaces
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• v.19 no.4
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• pp.300-305
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• 2006

The problem of assigning customers to satellite channels is considered in this paper. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of GA with CPLEX8.1 is presented to show the advantages of this approach in terms of computation time and solution quality.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1042-1044
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• 2003

A methodology of the integrating the similar color circle search of the spectral data and segmentation of the height data is developed. The method is then applied to study areas, and the results by IKONOS, LIDAR and data fusion are verified with the ground truth, and examined in terms of the accuracy. Results show that with the data fusion the accuracy are improved by about 15% in most of the study areas. The methodology for the detection of individual tree stands by data fusion is explored, and the utility of combinatorial use of the spectral and the height information is demonstrated.