• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.40-46
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• 2015

The modular assembly system can make it possible for the variety of products to be assembled in a short lead time. In this system, necessary components are assembled to optional components tailor to customers' orders. Budget for inventory investments composed of inventory and purchasing costs are practically limited and the purchasing cost is often paid when an order is arrived. Service cost is assumed to be proportional to service level and it is included in budget constraint. We develop a heuristic procedure to find a good solution for a continuous review inventory system of the modular assembly system with a budget constraint. A regression analysis using a quadratic function based on the exponential function is applied to the cumulative density function of a normal distribution. With the regression result, an efficient heuristics is proposed by using an approximation for some complex functions that are composed of exponential functions only. A simple problem is introduced to illustrate the proposed heuristics.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.2
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• pp.236-247
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• 1992

Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.1-13
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• 2016

Fish mortality is the most important success factor in aquaculture management. To analyze the effect of mortality considering biological and economic condition is a important problem in land-based aquaculture. This study is aimed to analyze the effect of mortality for duration of cultivation in land-based aquaculture. This study builds the mathematical model that finds the value of decision variable to minimize cost that sums up the water pool usage cost, sorting cost, fingerling cost and feeding cost under critical standing corp constraint. The proposed mathematical model involves many aspects, both biological and economical: (1) number of fingerlings (2) timing and number of batch splitting event, based on (3) fish growth rate, (4) mortality, and (5) several farming expense. Numerical simulation model presented here in. The objective of numerical simulation is to provide for decision makers to analyse and comprehend the proposed model. When extensive biological and cost data become available, the proposed model can be widely applied to yield more accurate results.

• The Journal of Fisheries Business Administration
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• v.48 no.3
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• pp.47-59
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• 2017

Fish mortality is the most important success factor in aquaculture management. To order fingerlings considering the effect of mortality is a important problem in aquaculture farm. This study is aimed to decision the number and size of fry in aquaculture farm. This study build the mathematical model that finds the value of decision variable to minimize total cost that sums up the fingerling purchasing cost, aquaculture farm operating cost and feeding cost under mortality constraint. The proposed mathematical model involve biological and economical variables: (1) number of fingerlings (2) fish growth rate (3) mortality (4) price of a fry (5) feeding cost, and (6) possible order period. Numerical simulation model presented here in. The objective of numerical simulation is to provide for decision makers to analyse and comprehend the proposed model. When extensive biological and cost data become available, the proposed model can be widely applied to yield more accurate results.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1508-1517
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• 2015

Optimal Power dispatch is the short-term decision of the optimal output of a number of power generation facilities, to meet the system demand, with the objective of Power dispatching at the lowest possible cost, subject to transmission lines power loss and operational constraints. The operational constraint includes power balance constraint, generator limit constraint, and emission dispatch constraint and valve point effects. In this paper, Opposition based Differential Evolution Algorithm (ODEA) has been proposed to handle the objective function and the operational constraints simultaneously. Furthermore, the valve point loading effects and transmission lines power loss are also considered for the efficient and effective Power dispatch. The ODEA has unique features such as self tuning of its control parameters, self acceleration and migration for searching. As a result, it requires very minimum executions compared with other searching strategies. The effectiveness of the algorithm has been validated through four standard test cases and compared with previous studies. The proposed method out performs the previous methods.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.345-375
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• 2002

The purpose of this paper is to measure the change of the production efficiency which may happen when environmental regulation incurs technological constraint in the process of production, and to compute the opportunity cost of pollution reduction with the lost products based on the change of efficiency. The patterns of production technoloy in the paper are divided into the technologies of strong disposability and weak disposabilty to grasp the effect of the technological constraint due to the environmental regulation. The endowment of the technolgical constraints in the process of production is considered to bring the greatest restriction on firm's production. When the environmental efficiencies of Korean regional manufactures were measured with linear programming model, the lost products related with the constraint of production technology that environmental regulation incurred, was average 148.1 billion dollar per year(5.87% of one year overall products) for total manufactures in 1991~1998. The ratio of the lost products for total products was spread from 0.78% to 1l.08%. The average lost products of 15 regions were changed from 4.66% to 18.35% of total products. Generally the environmental efficiency index of regional manufactures being decreased continuously since 1991, it is estimated that the environmental performance of Korean manufactures has been more and more deteriorating.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.3053-3060
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• 2000

Alternative formulation is presented for robust optimization problems and an efficient computational scheme for reliability estimation is proposed. Both design variables and design parameters considered as random variables about their nominal values. To ensure the robustness of objective performance a new cost function bounding the performance and a new constraint limiting the performance variation are introduced. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub-optimization problem and then is resolved with the modified advanced first order second moment(AFOSM) method for computational efficiency. The proposed robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required even in case of gradient based optimization. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• The Journal of Information Systems
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• v.27 no.4
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• pp.203-227
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• 2018

Purpose The purpose of this study is to investigate which decision factors continue to use the service based on the online simple payment service. In this study, we will examine how to activate the service from the continuing factors through the dual-model theory consisting of personal dedication and constraint dedication which are frequently used in relation marketing. Design/methodology/approach In this study, we investigated the activation of online simple settlement service using factors affecting the preference of the simple payment service based on the dual-model of dedication-based mechanism and constraint-based mechanism. Findings This study confirmed that customer satisfaction and convenience under the dedication -based mechanism were found to be linked to the preference of the simple payment service. Switching cost under the constraint - based mechanism showed that the customer had no binding ability to continue using the service of the current provider. Likewise, preference was found to have a direct effect on the actual frequency of use of the simple payment service, the number of uses compared to the total number of online payments, and willingness to use more.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1261-1267
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• 2013

In multibody mechanical systems, low-degree-of-freedom (DOF) joints such as revolute and translational joints are much more frequently used than high-DOF joints. In order to formulate kinematic constraint equations, especially for low-DOF joints, in an efficient and systematic manner, this paper presents a parametric generalized coordinate formulation as a new approach for describing constraint equations. In the proposed approach, joint constraint equations are formulated in terms of a mixed set of Cartesian and parametric generalized coordinates, which drastically reduces the complexity and computational cost of the partial derivatives of the constraints such as the constraint Jacobian. The proposed formulation is validated using a simple cylinder-crank system with an implicit integrator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.6
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• pp.587-593
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• 2016

Reliability-based design optimization (RBDO) requires a high computational cost owing to its reliability analysis. A surrogate model is introduced to reduce the computational cost in RBDO. The accuracy of the reliability depends on the accuracy of the surrogate model of constraint boundaries in the surrogated-model-based RBDO. In earlier researches, constraint boundary sampling (CBS) was proposed to approximate accurately the boundaries of constraints by locating sample points on the boundaries of constraints. However, because CBS uses sample points on all constraint boundaries, it creates superfluous sample points. In this paper, efficient constraint boundary sampling (ECBS) is proposed to enhance the efficiency of CBS. ECBS uses the statistical information of a kriging surrogate model to locate sample points on or near the RBDO solution. The efficiency of ECBS is verified by mathematical examples.