• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.105-114
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• 2022

We examine berth allocation problems in tidal bulk ports with an objective of minimizing the demurrage and dispatch associated berthing cost. In the proposed optimization model inventory (or stock) level constraints are considered so as to satisfy the service level requirements in bulk terminals. It is shown that the mathematical programming formulation of this research provides improved schedule resolution and solution accuracy. We also show that the conventional big-M method of standard resource allocation models can be exempted in tidal bulk ports, and thus the computational efficiency can be significantly improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.155-161
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• 2020

In general, optimization problems are difficult to solve simply. The reason is that the given problem is solved as soon as it is simple, but the more complex it is, the very large number of cases. This study is about the optimization of AI neural network. What we are dealing with here is the relief method for constructing AI network. The main topics deal with non-deterministic issues such as the stability and unstability of the overall network state, cost down and energy down. For this one, we discuss associative memory models, that is, a method in which local minimum memory information does not select fake information. The simulated annealing, this is a method of estimating the direction with the lowest possible value and combining it with the previous one to modify it to a lower value. And nonlinear planning problems, it is a method of checking and correcting the input / output by applying the appropriate gradient descent method to minimize the very large number of objective functions. This research suggests a useful approach to relief method as a theoretical approach to solving optimization problems. Therefore, this research will be a good proposal to apply efficiently when constructing a new AI neural network.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.365-372
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• 2021

This paper deals with an optimal Weapon-Target Assignment (WTA) algorithm for Closed-In Weapon Systems (CIWS), considering variable burst time. In this study, the WTA problem for CIWS is formulated based on Mixed Integer Linear Programming (MILP). Unlike the previous study assuming that the burst time is fixed regardless of the engagement range, the proposed method utilizes the variable burst time based on the kill probability according to the engagement range. Thus, the proposed method can reflect a more realistic engagement situation and reduce the reaction time of CIWS against targets, compared to the existing method. In this paper, we first reformulate the existing MILP-based WTA problem to accommodate the variable burst Time. The proposed method is then validated through numerical simulations with the help of a commercial optimization tool.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.131-136
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• 2015

The chemical tank loading problem has been classified as nondeterministic polynomial time (NP)-complete problem because of the polynomial-time algorithm to find the solution has been unknown yet. Gu$\acute{e}$ret et al. tries to obtain the optimal solution using linear programming package with $O(m^4)$ time complexity for chemical tank loading problem a kind of bin packing problem. On the other hand, this paper suggests the rule of loading chemical into minimum margin tank algorithm with O(m) time complexity. The proposed algorithm stores the chemical in the tank that has partial residual of the same kind chemical firstly. Then, we load the remaining chemical to the minimum marginal tanks. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(m) time complexity for NP-complete chemical tank loading problem.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.26.3-27
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• 2009

한 기의 영상레이더 위성을 이용하여 동일한 촬영지역에 대해 적절한 기선벡터(Baseline)을 유지하는 두 장(scene)의 영상을 획득하여 그 지역의 정밀 표고차를 추출하는 레이더 간섭계(Interferometry) 임무를 수행하기 위해서는 반복지상궤적을 유지하도록 위성의 궤도를 주기적으로 조정해 주어야 한다. 이 연구에서는 반복지상궤적 유지 정밀도를 극대화시키기 위하여 최적의 기준궤도를 생성하고 이를 유지하기 위한 속도증분 및 궤도 조정 일정을 산출할 수 있는 궤도최적화 S/W 를 개발하였다. 이 연구의 최적 궤도 설계 문제는 다음과 같다. "시작시간 $T_0$에서 초기 접촉궤도 상태벡터 (ECEF 위치 및 속도벡터) $x_0$이고, 지상궤적반복주기 p 이후의 시간 $T_0+p$에서도 초기 접촉궤도 상태벡터와 동일한$x_0$가 되도록 궤도를 유지하려고 할 때, 여명 궤도(dawn-dusk and sun-synchronous orbit)에서 운영되는 위성의 연료소모(또는 속도증분)를 최소화시키는 가상의 궤도조정(maneuver) 횟수, 시기, 크기를 찾아라." 이 연구에서는 궤도최적화 문제를 풀기 위하여 GRACE 중력모델(GGM02C)이 적용된 수치적 방법의 위성궤도예측 알고리즘을 시스템 설계에 적용하였고, 매개변수 최적화 방법 중 구속조건이 있는 비선형 최적화 기법의 하나인 연속 2차 계획법(sequential quadratic programming)을 사용하여 해를 구하였다. 개발된 궤도최적화 S/W의 성능을 분석하기 위하여 고도 550km의 여명궤도를 돌며 지상궤적반복주기가 28일인 영상레이더 위성에 대해 적용하였다. 해석 결과를 통해, 비록 시스템의 비선형이 큼에도 불구하고 최소의 속도증분으로 정밀한 반복지상궤적이 유지됨을 알 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.169-173
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• 2014

Nobody has yet been able to determine the optimal solution conclusively whether NP-complete problems are in fact solvable in polynomial time. Gu$\acute{e}$ret et al. tries to obtain the optimal solution using linear programming with $O(m^4)$ time complexity for barge loading problem a kind of bin packing problem that is classified as nondeterministic polynomial time (NP)-complete problem. On the other hand, this paper suggests the loading rule of profit priority rank algorithm with O(m log m) time complexity. This paper decides the profit priority rank firstly. Then, we obtain the initial loading result using the rule of loading the good has profit priority order. Finally, we balance the loading and capability of barge swap the goods of unloading in previously loading in case of under loading. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(m log m) time complexity for NP-complete barge loading problem.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.123-133
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• 2006

The main objective of this study is to develop an optimization algorithm of framed structures with rigid and various semi-rigid connections using the multilevel dynamic programming and the sequential unconstrained minimization techniques (SUMT). The second-order elastic analysis is performed for steel framed structures. The second order elastic analysis is developed based on nonlinear beam-column theory considering the bowing effect. The following semi-rigid connections are considered; double web angle, top-seat angle and top-seat angle with web angle. We considered the three connection models, such as modified exponential, polynomial and three parameter model. The total weight of the structural steel is used as the objective function in the optimization process. The dimensions of steel cross section are selected as the design variables. The design constraints consist of strength requirements for axial, shear and flexural resistance and serviceability requirements.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.189-195
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• 2021

This paper discusses choice of loans problem(CLP) that is to minimize annual payment from which bank's borrows in multi-banks multi-nations with distinct interests. For the CLP, there is impossible to obtain the optimal solution actually without the help of mathematical software package as linear programming(LP). This paper applies the method used in transportation problem(TP) that finds initial feasible solution with selects minimum interest first, least cost method(LCM), to CLP. Result of experiment, the proposed algorithm can be obtains the optimal solution with at most two exchange optimization for LCM's initial feasible solution.

• Computational Structural Engineering
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• v.1 no.1
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• pp.87-94
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• 1988

The linerization method as one of the recursive quadratic programming method is applied for the optimal design of a large-scale structure supported by Pshenichny's proof of global convergence of the algorithm and convergence rate estimates. The linearization method transforms all constants of the design problem into an equivalent linearized constraint and employs the active-set strategy. This results in substantial computational savings by reducing the number of sate and adjoint to be solved at every design iteration. The illustrative example of plates with beams supported by columns is the typical one of a large-scale structure to give successful optimum solutions with satisfactory convergence criteria. Hopefully, the method may be applicable to all classes of optimization problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.4
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• pp.361-371
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• 2012

In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a nonuniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The suggested scheme assigns the convergence tolerances for each continuous subproblem optimization according to the maximum constraint violation obtained from the first iteration of each subproblem optimization in order to reduce the total number of function evaluations needed to reach the discrete optimal solution. The proposed tolerance scheme is integrated with five branching order options. The comparative performance test results using the ten combinations of the five branching orders and two convergence tolerance schemes show that the suggested non-uniform convergence tolerance scheme is obviously superior to the uniform one. The results also show that the branching order option using the minimum clearance difference method performed best among the five branching order options. Therefore, we recommend using the "minimum clearance difference method" for branching and the "non-uniform convergence tolerance scheme" for solving discrete optimization problems.