• Korean Management Science Review
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• v.17 no.2
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• pp.115-124
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• 2000

Activity-Based Costing(ABC) is an accounting cost system which allocates the overhead cost to each cost object more accurately. ABC system achieves improved accuracy in estimating the cost of cost object by using multiple cost drivers to trace the cost of activities to the cost objects associated with the resources consumed by those activities. The selection and the aggregation of these cost driver candidates can pose difficult problems. This paper deals with these problems in mathematical programming approach. The first model is formulated as an integer programming model in cost driver selection and the second model is formulated as multi-objective goal programming model in reduction of cost drivers already selected.

• Journal of Korean Society for Quality Management
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• v.8 no.2
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• pp.15-22
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• 1980

This paper deals with the problem of determining a minimum cost sampling inspection plan for a single destructive testing by attribute. The cost for inspection lot is constructed by following three cost factors: (1) cost of inspection, (2) cost of accepted defective, (3) cost of rejected lot Using Hald's Bayesian approach in a single non-destructive testing, procedure's for finding the minimum cost single destructive sampling inspection plan by attribute are given. Assuming the uniform distribution as a prior-distribution and using numerical analysis by computer, a minimum cost single destructive sampling inspection plan by attribute for several lot sizes, unit cost, destructive testing cost, and salvage cost is given.

• Korean Journal of Agricultural Science
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• v.37 no.2
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• pp.245-248
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• 2010

This study was conducted to investigate effect of changes in target fat and protein contents in milk on feed cost using a simulation modeling approach based on the 2001 dairy NRC. Two simulations were done; simulation I had a limitation (up to 20%), but simulation II had no limitation for the use of cottonseed hull in a diet. Using commonly used feed ingredients in Korea, we formulated least cost diets that meet nutrient requirement of a lactating dairy cow producing 36 kg of milk with combinations of 0.1% decrease or 0.1% increase in target milk fat or protein, respectively, from the national average milk fat (4.0%) and milk protein (3.1%). The contents of alfalfa and corn in a least-cost diet were decreased and those of tall fescue, whole cottonseed and rapeseed meal were increased with decreasing fat and/or increasing protein in milk. Scenarios that decreased target milk fat percentage from 4.0% to 3.9% reduced feed cost by 2 won per kg. Due to decrease in feed intake, daily feed cost was even more reduced (136 won per head) by decreasing target milk fat percentage. Increase in target milk protein percentage from 3.1% to 3.2% reduced feed cost by 6 won per kg. Among scenarios simulated, the least feed cost was obtained in scenario aimed for 3.9% fat and 3.2% of protein in milk. We conclude that a feeding practice for increasing milk protein percentage does not directly increase feed cost. In addition, feeding practices that increase protein content in milk is expected to improve economic life-span and reproductive performance of dairy cows.

• Korean System Dynamics Review
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• v.3 no.2
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• pp.113-140
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• 2002

The cost-benefit analysis is a technique for assisting with decision about the use of society's scare resources. There exists no detailed assessment like cost-benefit analysis. But recently, many policy analysts criticized the merit of cost-benefit analysis. As it is, it can be said that partial or approximate estimates of benefit and cost may be more dangerous than helpful. The purpose of this study is to overcome the limit of traditional cost-benefit analysis. For this purpose, we use the system dynamics approach for setting up new cost-benefit analysis, which we named that ‘Dynamics Cost-Benefit Analysis'. The usefulness of ‘Dynamics Cost-Benefit Analysis' is as follows; finding structural causal relationship between cost factors and benefit factors, understanding the long-term behavior of systems economic feasibility. In this study, we apply 'Dynamic Cost-Benefit Analysis' to case that is construction investment of funeral house by local government sector.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.207-216
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• 2000

This paper introduces an effective system design method to develop a customer oriented product using a design optimization process and to select a set of critical design paramenters,. The process results in the development of a successful product satisfying customer needs and reducing development risk. The proposed scheme adopted a five step QFD(Quality Function Deployment) in order to extract design parameters from customer needs and evaluated their priority using risk factors for extracted design parameters. In this process we determine critical design parameters and allocate them to subsystem designers. Subsequently design engineers develop and test the product based on these parameters. These design parameters capture the characteristics of customer needs in terms of performance cost and schedule in the process of QFD, The subsequent risk management task ensures the minimum risk approach in the presence of design parameter uncertainty. An application of this approach was demonstrated in the development of weld quality monitoring system. Dominant design parameters affect linearity characteristics of weld defect feature vectors. Therefore it simplifies the algorithm for adopting pattern classification of feature vectors and improves the accuracy of recognition rate of weld defect and the real time response of the defect detection in the performance. Additionally the development cost decreases by using DSP board for low speed because of reducing CPU's load adopting algorithm in classifying weld defects. It also reduces the cost by using the single sensor to measure weld defects. Furthermore the synergy effect derived from the critical design parameters improves the detection rate of weld defects by 15% when compared with the implementation using the non-critical design parameters. It also result in 30% saving in development cost./ The overall results are close to 95% customer level showing the effectiveness of the proposed development approach.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.3
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• pp.31-38
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• 2019

In this paper, we design a green supply chain (gSC) network model. For constructing the gSC network model, environmental and economic factors are taken into consideration in it. Environmental factor is to minimize the $CO_2$ emission amount emitted when transporting products or materials between each stage. For economic factor, the total cost which is composed of total transportation cost, total handling cost and total fixed cost is minimized. To minimize the environmental and economic factors simultaneously, a mathematical formulation is proposed and it is implemented in a genetic algorithm (GA) approach. In numerical experiment, some scales of the gSC network model is presented and its performance is analyzed using the GA approach. Finally, the efficiencies of the gSC network model and the GA approach are proved.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.246-248
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• 2006

This paper is concerned with non-fragile guaranteed cost state feedback controller design algorithm for descriptor systems with time-varying delay and static state feedback controller with multiplicative uncertainty. The considered uncertainties are norm-bounded and time delay is time-varying. Under the condition of controller gain variations, conditions for the existence of controller satisfying asymptotic stability and non-fragility and controller design method are derived via LMI approach. Moreover, the measure of non-fragility and the upper bound to minimize guaranteed cost function are given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.231-241
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• 1999

Recent market competition forces the price to be determined in the design stage so that the design would meet the target price of the product. However, most commercial PDM(Product Data Management) systems currently in use lack such a cost estimation function. In this paper, we propose detailed structure and functions of a new approach to estimate the cost of new products using integrated BOM in PDM. Such system will reduce the total life cycle cost of the products to be designed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.31-37
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• 2013

In this paper, we develop an efficient approach to solve a continuous review inventory system with a budget constraint when the semi-finished product and optional components are required to be assembled. We are, in particular, interested in a budget constraint that includes a service level. The service cost, such as labor and facility costs, tends to increase as the service level increase, and it makes the problem difficult to solve. Assuming that the reorder point for a semi-finished product is given, we show that the order quantity for the semi-finished product and the order quantity and reorder point for optional components can be determined by minimizing the total cost that includes setup cost, inventory holding cost, and shortage cost. The performance of the proposed approach is tested by numerical examples. By using sensitivity analysis, we conclude that, as the reorder point for semi-finished product increases, the order quantity for semi-finished product increases, whereas the order quantity and reorder point of optional components decreases.