• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.57-62
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• 2006

The quality of precision spindle units (S/Us) running on rolling bearings depends strongly on their structural parameters, such as the configuration and geometry of the S/U elements and bearing preloads. When S/Us are designed, their parameters should be optimized to improve the performance characteristics. However, it is practically impossible to state perfectly a general criterion function for S/U quality. Therefore, we propose to use a multicriteria optimization based on the parameter space investigation (PSI) method We demonstrate the efficiency of the proposed method using the optimization results of high-speed S/Us.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Bulletin of the Korean Mathematical Society
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• v.49 no.2
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• pp.249-262
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• 2012

In this paper, under some suitable conditions and in virtue of a selection which depends on a vector-valued function and a feasible set map, the sensitivity analysis of a class of implicit multifunctions is investigated. Moreover, by using the results established, the solution sets of parametric vector optimization problems are studied.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.361-371
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• 2000

This paper treats a genetic algorithm for ship scheduling problem in set packing formulation. We newly devised a partition based representation of solution and compose initial population using a domain knowledge of problem which results in saving calculation cost. We established replacement strategy which makes each individual not to degenerate during evolutionary process and applied adaptive mutate operator to improve feasibility of individual. If offspring is feasible then an improve operator is applied to increase objective value without loss of feasibility. A computational experiment was carried out with real data and showed a useful result for a large size real world problem.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1004-1007
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• 1992

In this paper, we present a solution to the PID tuning problem by optimizing a GPC(General Predictive Control) criterion. The PID structure is ensured by constraning the parameters to a feasible set defined by the discrete-time Euler approximation of the ideal continuous-time PID controller. The algorithm is ectended by incorporating heuristic rules for selection of the significant design parameters. The algorithm has been successfully tested and some results are prewented.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.45-60
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• 2005

This paper investigates the application of the computer method COMSOAL (Computer Method of Sequencing Operations for Assembly Lines) to the process routing (PR) problem with multiple objectives. In any computer aided process planning (CAPP) system, one of the most critical activities for manufacturing a part could be to generate the sequence that optimizes production time, production cost, machine utilization or with multiple these criteria. The COMSOAL has been adopted to find the optimum sequence of operations that optimizes two major conflicting criteria : production cost and production quality. The COMSOAL is here slightly modified to simultaneously generate and evaluate a set of possible solutions (called as population) instead of processing a solution stepwise in each iteration. The significant features of the COMSOAL include : no parameters settings needed, and a guarantee of feasible solutions. Experimental results show that COMSOAL is a simple but powerful method to quickly generate multiple feasible solutions which are as good as the ones obtained from several other well-known process routing algorithms.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1195-1198
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• 1999

This paper presents optimal placement of minimal set of phasor measurement units(PMU's) and observability of measurement system with PMU. By using the incidence matrix symbolic method which directly assigns measurement and pseudo-measurement to incidence matrix, it is much simpler and easier to analyze observability. The optimal PMU set is found through the simulated-annealing(SA) and the direct combinational method. The cooling schedule parameter which is suitable to the property of problem to solve is specified and optimal placement is proven by presented direct combinational method. Search spaces are limited within reasonable feasible solution region to reduce a unnecessary one in the SA implementation based on global search. The proposed method presents to save CPU time and estimate state vectors based on optimal PMU set.

• Advances in Computational Design
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• v.2 no.3
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• pp.195-210
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• 2017

Simultaneous optimization of trusses which concurrently takes into account design variables related to the size, shape and topology of the structure is recognized as highly complex optimization problems. In this class of optimization problems, it is possible to encounter several unstable mechanisms throughout the solution process. However, to obtain a feasible solution, these unstable mechanisms somehow should be rejected from the set of candidate solutions. This study proposes triangular unit based method (TUBM) instead of ground structure method, which is conventionally used in the topology optimization, to decrease the complexity of search space of simultaneous optimization of the planar truss structures. TUBM considers stability of the triangular units for 2 dimensional truss systems. In addition, integrated particle swarm optimizer (iPSO) strengthened with robust technique so called improved fly-back mechanism is employed as the optimizer tool to obtain the solution for these class of problems. The results obtained in this study show the applicability and efficiency of the TUBM combined with iPSO for the simultaneous optimization of planar truss structures.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.1-8
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• 2008

Automatic parking assist system is one of the key technologies of the future automobiles. Control problem of a car-like vehicle is not easy due to the nonholonomic constraints. In this paper, a practical solution for planning a car-parking path is proposed according to the proposed motion space (M-space) approach. The M-space is the extension of the conventional configuration space (C-space). A collision-free, nonholonomic feasible path can be directly computed by the M-space conversion and a back-propagation of reachable regions from the goal. The proposed planning scheme provide not a single solution, but also a candidate solution set, therefore, optimization of the parking path can be easily carried out with respect to performance criteria such as safety, maneuvering, and so on. Presented simulation results clearly show that the proposed scheme provides various practical solutions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.83-86
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• 1996

In this paper we study the problem of augmenting a physical network to improve the topology for new survivable network architectures. We are given a graph G=(V,E,F), where V is a set of nodes that represents transmission systems which be interconnected by physical links, and E is a collection of edges that represent the possible pairs of nodes between which a direct transmission link can be placed. F, a subset of E is defined as a set of the existing direct links, and E/F is defined as a set of edges for the possible new connection. The cost of establishing network $N_{H}$=(V,H,F) is defined by the sum of the costs of the individual links contained in new link set H. We call that $N_{H}$=(V,H,F) is feasible if certain connectivity constrints can be satisfied in $N_{H}$=(V,H,F). The computational goal for the suggested model is to find a minimum cost network among the feasible solutions. For a k edge (node) connected component S .subeq. F, we charactrize some optimality conditions with respect to S. By this characterization we can find part of the network that formed by only F-edges. We do not need to augment E/F edges for these components in an optimal solution. Hence we shrink the related component into a node. We study some good primal heuristics by considering construction and exchange ideas. For the construction heuristics, we use some greedy methods and relaxation methods. For the improvement heuristics we generalize known exchange heuristics such as two-optimal cycle, three-optimal cycle, pretzel, quezel and one-optimal heuristics. Some computational experiments show that our heuristic is more efficient than some well known heuristics.stics.