• Environmental and Resource Economics Review
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• v.19 no.4
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• pp.771-804
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• 2010

This paper estimates optimal production of fish stock using discrete time bio-economic model to make zero profits or to maximize economic profits with maintaining sustainable resource levels under an open access and a sole owner. Particularly, this study generates optimal yields and efforts of large purse seine fisheries which catch mackerel and jack mackerel by using the logistic growth function, Cobb-Douglas production function, fisheries cost and profit functions. As a result, optimal yields of mackerel and jack mackerel under ecological equilibrium of a sole owner were approximately 172,512 tons and 16,937 tons respectively. Also, optimal fishing efforts of mackerel and jack mackerel under the same situation were about 8,508 hauls and 4,915 hauls respectively. In conclusion, the paper suggests that the large purse seine should reduce fishing efforts and increase fish stock to generate higher net present value in optimally managed fishery than that of the present large purse seine.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1898-1909
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• 1993

In this paper, a convenient scheme for solving multi-objective optimization problems including fuzzy information in both objective functions and constraints is presented. At first, a multi-objective problem is converted into single objective problem based on the norm method, and a merbership function is constructed by selecting its type and providing the parameters defined by the norm method. Finally, this fuzzy programming problem is converted into an ordinary optimization problem which can be solved by usual nonlinear programming techniques. With this scheme, a designer can conveniently obtain pareto optimal solutions of a fuzzy system only by providing some parameters corresponding to the importance of the objectiv functions. Proposed scheme is simple and efficient in treating multi-objective fuzzy systems compared with and method by with membership function value is provided interactively. To show the validity of the scheme, a simple 3-bar truss example and optimal cutting problem are solved, and the results show that the scheme is very useful and easy to treat multi-objective fuzzy systems.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.38-44
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• 1994

Control Algorithms of the Auto-Pilot system have been studied for the navigational economics and crew's comfortability since 1960's, when Auto-Pilot system was installed on the trans-ocean ships. At the beginning the PD control algorithm was used with the weather adjust function introduced to reduce the response of the auto-pilot system to the high frequency wave excitation in rough sea. In this study, the optimal and adaptive control theories are applied for the auto-pilot control algorithm. And those two algorithms are compared through the pre-defined cost function to obtain the most effective control technique for the Auto-Pilot system. The parameterization of the ship meneuvering equation for the adaptive control algorithm design procedure was examined and the advantage of the adaptive control was found through the simulation result with the wrong initial parameter value.

• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.183-190
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• 2021

Tomographic particle image velocimetry (PIV) is a widely used method that measures a three-dimensional (3D) flow field by reconstructing camera images into voxel images. In 3D measurements, the setting and calibration of the camera's mapping function significantly impact the obtained results. In this study, a camera self-calibration technique is applied to tomographic PIV to reduce the occurrence of errors arising from such functions. The measured 3D particles are superimposed on the image to create a disparity map. Camera self-calibration is performed by reflecting the error of the disparity map to the center value of the particles. Vortex ring synthetic images are generated and the developed algorithm is applied. The optimal result is obtained by applying self-calibration once when the center error is less than 1 pixel and by applying self-calibration 2-3 times when it was more than 1 pixel; the maximum recovery ratio is 96%. Further self-correlation did not improve the results. The algorithm is evaluated by performing an actual rotational flow experiment, and the optimal result was obtained when self-calibration was applied once, as shown in the virtual image result. Therefore, the developed algorithm is expected to be utilized for the performance improvement of 3D flow measurements.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.786-792
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• 2009

Topology optimization is to find the optimal material distribution of the specified design domain minimizing the objective function while satisfying the design constraints. Since the genetic algorithm (GA) has its advantage of locating global optimum with high probability, it has been applied to the topology optimization. To guarantee the structural connectivity, the concept of compliance pattern is proposed and to improve the convergence rate, small number of population size and variable probability in genetic operators are incorporated into GA. The rank sum weight method is applied to formulate the fitness function consisting of compliance, volume, connectivity and checkerboard pattern. To substantiate the proposed method design examples in the previous works are compared with respect to the number of function evaluation and objective function value. The comparative study shows that the compliance pattern based GA results in the reduction of computational cost to obtain the reasonable structural topology.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.65-85
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• 2024

The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.873-882
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• 2010

This paper considers a Bayesian approach to replacement policy following the expiration of non-renewing combination warranty. The non-renewing combination warranty is the combination of the non-renewing free replacement warranty and the non-renewing pro-rata replacement warranty. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure times are assumed to follow a Weibull distribution with uncertain parameters, we propose the optimal replacement policy based on the Bayesian approach. The overall value function suggested by Jiang and Ji (2002) is utilized to determine the optimal replacement period. Also, the numerical examples are presented for illustrative purpose.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.732-737
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• 2001

The mathematical method was developed and numerical analyses were carried out with various parameters to provide substantial data for optimal design and operation of urban utility systems. The composition of systems and their specifications, such as co-generation system, heat pump system, incineration system and other heating and cooling system could be obtained through these analyses for various resource and energy requirements in urban area. As results the system constituents and operating characteristics, and their economic performances such as the value of objective function, initial and an operating costs were discussed for various load patterns. The effective system design method and the excepted effects of the several unused energy recovery systems were also briefly discussed with the variation of the buildings and facilities species and their capacities.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.42 no.3
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• pp.190-196
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• 2009

To optimize the mixing ratio of ingredients for optimal sensory qualities of seasoned tofu, a response surface methodology with a central composite design was performed on tofu containing freshwater crab meat (TCM). Using the desirability function technique, the optimal formulation was determined to be 3.67 g of freeze dried meat, 5.54 g of garlic powder, and 2,120 mL of soymilk. In the texture profile analysis, tofu prepared using the optimal ingredient ratio had a higher hardness, cohesiveness and gumminess than commercial tofu but TCM value for adhesiveness, springiness and chewiness were lower. However, the texture properties of TCM were not significantly different than those of commercial tofu.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.