• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.145-158
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• 2005

We formulate a stochastic control problem on proportional reinsurance that includes impulse and regular control strategies. For the first time we combine impulse control with regular control, and derive the expected total discount pay-out (return function) from present to bankruptcy. By relying on both stochastic calculus and the classical theory of impulse and regular controls, we state a set of sufficient conditions for its solution in terms of optimal return function. Moreover, we also derive its explicit form and corresponding impulse and regular control strategies.

• 대한수학회보
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• 제56권5호
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• pp.1211-1217
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• 2019

Let $0<{\alpha}<{\infty}$ be fixed, and let $X=(X_t)_{t{\geq}0}$ be a Bessel process with dimension $0<{\theta}{\leq}1$ starting at $x{\geq}0$. In this paper, it is proved that there are positive constants A and D depending only on ${\theta}$ and ${\alpha}$ such that $$E_x\({\exp}[{\alpha}\;\max_{0{\leq}t{\leq}{\tau}}\;X_t]\){\leq}AE_x\({\exp}[D_{\tau}]\)$$ for any stopping time ${\tau}$ of X. This inequality is also shown to be sharp.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• 해양환경안전학회지
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• 제3권2호
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• pp.93-103
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• 1997

This paper develops a new heuristic, the Excursion Algorithm(EA), for constructing optimal designs for the experiments related with marine environment. The proposed EA consists of three parts: 1) construction of an initial feasible solution, 2) excursions over a bounded region, and 3) stopping rules. It is the second part that distinguishes the EA from the other existing heuristic methods. It turns out that excursions over a bounded feasible and/or infeasible region is effective in alleviating the risks of being trapped at a local optimum. Since this problem is formulated for the first time thesis, other heuristic algorithms do not exist. Therefore, global optimal solutions are obtained by complete enumeration for some cases, and the performance of the EA is evaluated in terms of solution quality. Computational results show that the proposed EA is effective in finding good(or, in many cases, global) solutions to the constrained optimal experimental design problems.

• 대한수학회보
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• 제48권4호
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• pp.791-812
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• 2011

This is a survey on American options. An American option allows its owner the privilege of early exercise, whereas a European option can be exercised only at expiration. Because of this early exercise privilege American option pricing involves an optimal stopping problem; the price of an American option is given as a free boundary value problem associated with a Black-Scholes type partial differential equation. Up until now there is no simple closed-form solution to the problem, but there have been a variety of approaches which contribute to the understanding of the properties of the price and the early exercise boundary. These approaches typically provide numerical or approximate analytic methods to find the price and the boundary. Topics included in this survey are early approaches(trees, finite difference schemes, and quasi-analytic methods), an analytic method of lines and randomization, a homotopy method, analytic approximation of early exercise boundaries, Monte Carlo methods, and relatively recent topics such as model uncertainty, backward stochastic differential equations, and real options. We also provide open problems whose answers are expected to contribute to American option pricing.

• 대한산업공학회지
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• 제32권1호
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• pp.9-17
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• 2006

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

• 대한안전경영과학회지
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• 제5권1호
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• pp.69-82
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• 2003

The sequence which minimizes overall utility work in car assembly lines reduces the cycle time, the number of utility workers, and the risk of conveyor stopping. This study suggests mathematical formulation of the sequencing problem to minimize overall utility work, and present a genetic algorithm which can provide a near optimal solution in real time. To apply a genetic algorithm to the sequencing problem in car assembly lines, the representation, selection methods, and genetic parameters are studied. Experiments are carried out to compare selection methods such as roullette wheel selection, tournament selection and ranking selection. Experimental results show that ranking selection method outperforms the others in solution quality, whereas tournament selection provides the best performance in computation time.

• 터널과지하공간
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• 제24권1호
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• pp.11-20
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• 2014

본 연구에서는 노천광산에서 다수의 작업 지점들을 경유하며 광산 전역을 순회해야하는 보조 작업 차량의 최적 이동경로를 분석하였다. Dijkstra's 알고리즘을 사용했던 기존의 연구들과 달리 휴리스틱 외판원 문제 알고리즘을 이용한 결과 다수의 작업지점들의 방문 순서까지 고려하여 보조 작업 차량의 최적 이동경로를 분석할 수 있다. 인도네시아 파시르 석탄 노천광산의 로또 채광장을 대상으로 광산 전역을 정차 없이 순회하는 보조작업 차량의 최적 이동경로를 분석하였다. 그 결과 분석자의 직관에 따라 작업지점들의 방문 순서를 결정하는 것보다 휴리스틱 TSP 알고리즘을 적용해 분석하는 것이 25개 지점 경유시 20분 정도의 이동시간을 단축할 수 있는 것으로 분석되었다. 본 연구에서 제시한 결과가 노천광산 보조 작업 차량들의 시스템 최적화와 관련된 향후 연구들의 방향설정 위해 기초자료로 활용될 수 있을 것이라 기대한다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2009년도 추계학술대회
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• pp.131-135
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• 2009

This paper considers the sequencing of products in car assembly lines. The sequence which minimizes overall utility work in car assembly lines reduce the cycle time and the risk of conveyor stopping. The sequencing problem is solved using Tabu Search. Tabu Search is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality and computation time. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

• 한국ITS학회 논문지
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• 제8권5호
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• pp.26-37
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• 2009

본 연구에서는 USN 환경하에서 다수 개의 지점교통센서를 신호교차로의 접근로에 설치되어 운전자 안전서비스를 제공할 경우 딜레마구간 검지를 위한 센서의 배치 방법에 대하여 다룬다. 교통 신호가 녹색-황색-적색으로 변동되는 시점에서 딜레마구간에 존재하는 위험차량을 검지하는 시스템에서, 센서의 배치 간격과 초기 위치를 확인하기 위해 미시적 시뮬레이션인 VISSIM을 이용하여 평가하였다. VISSIM에 지점검지기를 다수 개 설치하여 유입교통량의 변화, 설계속도의 변화, 운전자 인지반응시간의 변화를 수행하였다. 그 결과 지점교통센서는 20~27m의 간격으로, 도로의 설계속도에 따라 초기 센서의 위치를 변화하여 설치할 필요성이 있음을 알 수 있었다. 또한 교통량의 변화에 따라 센서의 딜레마구간 검지추세가 다름을 알 수 있었다. 본 연구로 미시적 교통시뮬레이션 기반으로 지점교통센서의 배치를 평가하는 방법의 유용성을 확인할 수 있었고, 향후 USN 서비스의 실현에 있어 기초 자료로 사용될 수 있음을 알 수 있었다.