• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.3
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• pp.24-29
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• 2009

In case of the optimization problems that have many design variables, the conventional genetic algorithms(GA) fall into a trap of local minima with high probability. This problem is called the premature convergence problem. To overcome it, the parallel genetic algorithms which adopt the migration mechanism have been suggested. But it is hard to determine the several parameters such as the migration size and the migration interval for the parallel GAs. Therefore, we propose a new method to determine the migration interval automatically in this paper. To verify its validity, it is applied to some traditional mathematical optimization problems and is compared with the conventional parallel GA. It is also applied to the optimal design of the brushless DC motor for an electric wheel chair which is a real world problem and has five design variables.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.113-122
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• 1998

In this paper we consider the CSP requirements determination problem of new equipment(machine) system. For the newly procured equipment systems, mathematical analyses are made for the system which is constructed with the consumable parts to derive the associated CSP requirement determination model in mathematical expression. Based on these analyses, a mathematical model is derived for making an optimal CSP requirement determination subject to tile constraint of satisfying any given operational availability limitation. We assume that the failure of a part follows a Poisson process. Firstly, the operational availability concept in CSP is defined and the relation between the general system availability and the operational availability is established. Secondly, the problem is formulated as the cost minimization problem that should satisfy the operational availability limitation, and then, using the generalized Lagrange multipliers method, the optimal solution procedure is derived.

• Korean Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.107-121
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• 1996

An optimization procedure is proposed to determine the optimal stacking sequence on the buckling of laminated composite plates with midplane symmetry under various loading conditions. Classical lamination theory is used for the determination of the critical buckling load of simply supported angle-ply laminates. Analysis is performed by the Galerkin method and Rayleigh-Ritz method. The approximate solution of buckling is replaced by the algorithms that produce generalized eigenvalue problem. Direct search technique is employed to solve the optimization problem effectively. A series of computations is carried out for plates having different aspect ratios, different load ratios and different number of lay-ups.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.53-67
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• 2000

In this paper we consider the CSP requirements determination problem of new equipment(machine) system. For the newly procured equipment systems, mathematical analyses are made for the system which is constructed with the consumable parts and the repairable parts to derive the associated CSP requirement determination model in mathematical expression. Based on these analyses, a mathematical model Is derived for making an optimal CSP requirement determination subject to the constraint of satisfying any given operational availability limitation. We assume that the failure of a part follows a Poisson process and the repair time has an exponential distribution. Firstly, the operational availability concept in CSP is defined and the relation between the general system availability and the operational availability is established. Secondly, the problem is formulated as the cost minimization problem that should satisfy the operational availability limitation, and then, using the generalized Lagrange multipliers method, the optimal solution procedure Is derived.

• Design & Manufacturing
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• v.10 no.3
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• pp.8-13
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• 2016

Despite technological advance, there have been several troubles in photo reaction injection molding (photo RIM) to produce ultra thin light guide panels (LGPs). In this study, micro leakage problem at cavity edge during photo RIM was investigated numerically. In order to obtain optimal processing conditions, we regulated inlet pressure of injected resin at the cavity edge and figured out micro leakage behaviors. At low inlet pressure (less than 100 Pa), though the micro leakage problem was not occurred, another problem, short shot due to not enough driving force, was appeared More than 1,000 Pa of the inlet pressure, injected resin was rapidly leaked through the micro gap at the cavity edge. Finally, we obtained optimal inlet pressure around 600 ~ 1,000 Pa. At this region, injected resin fully filled the cavity without micro leakage behavior. Based on the present study, further comparative investigations with experimental photo RIM should be performed to find optimal processing conditions for produce ultra thin LGPs.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.987-1000
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• 2011

We show how the dynamic optimization problem with the capital constraint can be reduced to the problem to find an optimal modified claim $\tilde{\psi}H$ where $\tilde{\psi}$ is a randomized test in the static problem. Coherent risk measure is used as risk measure in the $L^{\infty}$ random variable spaces. The paper is written in expository style to some degree. We use an average risk of measure(AVaR), which is a special coherent risk measure, to see how to hedge the modified claim in a complete market model.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.197-199
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• 1999

This paper deals with optimal power flow, which is optimal problem with equality constraint and inequality constraint. A algorithm of changing two constraints problem to one constraint - equality constraint problem - that make it analytical access for optimal power flow is presented.

• Management Science and Financial Engineering
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• v.9 no.2
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• pp.47-68
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• 2003

We consider the customer order scheduling problem with job capacity restriction where the number of jobs in the shop at the same time is fixed. In the customer order scheduling problem, each job is part of some batch (customer order) and the composition of the jobs (product) in the batch is pre-specified. The objective function is associated with the completion time of the batches instead of the completion time of the jobs. We first summarize the known results for the general customer order scheduling problems. Then, we establish some new properties for the problems with job capacity restriction. For the case of unit processing time with the objective of minimizing makespan, we develop a polynomial-time optimal procedure for the two machine case. For the same problem with a variation of no batch alternation, we also develop a polynomial-time optimal procedure. Then, we show that the problems with the objectives of minimizing makespan and minimizing average batch completion time become NP-hard when there exist arbitrary number of machines. Finally, We propose optimal solution procedures for some special cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• Korean Journal of Construction Engineering and Management
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• v.8 no.6
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• pp.235-245
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• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.