• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.62-70
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• 2000

The design of gear train is a kind of mixed problems which have to determine various types of design variables; i,e., continuous, discrete, and integer variables. Therefore, the most common practice of optimum design using the derivative of objective function has difficulty in solving those kinds of problems and the optimum solution also depends on initial guess because there are many sophisticated constrains. In this study, the Genetic Algorithm is introduced for the optimum design of gear trains to solve such problems and we propose a genetic algorithm based gear design system. This system is applied for the geometrical volume(size) minimization problem of the two-stage gear train and the simple planetary gear train to show that genetic algorithm is better than the conventional algorithm solving the problems that have continuous, discrete, and integer variables. In this system, each design factor such as strength, durability, interference, contact ratio, etc. is considered on the basis of AGMA standards to satisfy the required design specification and the performance with minimizing the geometrical volume(size) of gear trains

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4B
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• pp.455-463
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• 2004

In this paper, we deal with a ring-mesh network design problem arising from the deployment of WDM for the optical internet. The ring-mesh network consists of ring topology and full mesh topology for satisfying traffic demand while minimizing the cost of OAOMs and OXCs. The problem seeks to find an optimal clustering of traffic demands in the network such that the total number of node assignments is minimized, while satisfying ring capacity and node cardinality constraints. We formulate the problem as a mixed-integer programming model and prescribe a tabu search heuristic procedure Promising computational results within 3% optimality gap are obtained using the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.481-488
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• 2008

This paper deals with a scheduling problem for two-machine flow shop, in which the preceding machine is a batch processing machine that can process a number of jobs simultaneously. To minimize makespan of the system, we present a mixed integer linear programming formulation for the problem, and using this formulation, it is shown that an optimal solution for small problem can be obtained by a commercial optimization software. However, since the problem is NP-hard and the size of a real problem is very large, we propose a number of heuristic algorithms including genetic algorithm to solve practical big-sized problems in a reasonable computational time. To verify performances of the algorithms, we compare them with lower bound for the problem. From the results of these computational experiments, some of the heuristic algorithms show very good performances for the problem.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.194-200
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• 2009

This study provides a heuristic algorithm to solve the locating problem of repair service centers (RSCs). To enhance the customer service level with more satisfaction and quicker responsiveness, the locating problem of RSCs has become one of the important issues in reverse supply chain management. This problem is formulated as a zero-one mixed integer programming in which an exiting distributor will be considered to be an un-capacitated repair service center for the objective of cost-minimizing. Since logistical costs are highly interrelated with the multinational location of distributors and RSCs, the fixed cost for setting a repair service center, variable cost, transportation cost, and exchange rates are considered in this study. Recognizing the selection of un-capacitated RSCs' locations is a combinatorial optimization problem and is a zero-one mixed integer programming with NP-hard complexity, we provide a heuristic algorithm named as incremental cost matrix procedure (ICMP) to simplify the solving procedure. By using the concise and structural cost matrix, ICMP can efficiently screen the potential location with cost advantage and effectively decide which distributor should be a RSC. Results obtained from the numerical experiments conducted in small scale problem have shown the fact that ICMP is an effective and efficient heuristic algorithm for solving the RSCs locating problem. In the future, using the extended ICMP to solve problems with larger industrial scale or problems with congestion effects caused by the variation of customer demand and the restriction of the RSC capacity is worth a further investigation.

• Journal of Korean Society of Transportation
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• v.31 no.2
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• pp.80-89
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• 2013

The purpose of this research is to optimize the line planning of the intercity passenger railway. In this study, the line planning problem has been formulated into a mixed integer programming by minimizing both user costs (passenger's total travel time) and operator costs (operation, maintenance and vehicle costs) with multiple train types. As a solution algorithm, the branch-and-bound method is used to solve this problem. The change of travel demand, train speed and the number of schedules have been tested through sensitivity analysis. The optimal stop-schedules and frequency as well as system split with respect to each train type have been found in the case study of Kyoung-bu railway line in Korea. The model and results of this research are useful to make a decision for railway operation strategy, to analyze the efficiency of new railway systems and to evaluate the social costs of users and operators.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.71-95
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• 2013

This study aims to validate the cost of building the infrastructure to commercialize online electric vehicles. For that purpose, we probe the cost to construct the necessary infrastructure for online electric vehicles regarding Seoul area public bus transit. OLEV and PEV are considered as alternative electric vehicle schemes, and each of them has their own cons and pros in terms of rechargeable battery cost and charger cost. An optimization model which minimizes the cost to install online electric bus feeding devices is proposed in order to compare the total costs of the two alternative schemes. We developed a Mixed Integer Programming model to locate the feeding devices of several different lengths at each bus stops. Furthermore, we implemented a computer simulator to obtain the parameters which will be used in the MIP model and a Web-based system which determines the optimal location of infrastructure for the whole city area from a result of the MIP model. The cost comparison result shows that the total cost of OLEV is cheaper than that of PEV considering the real data of Seoul area public transit, and, as a result, confirms the feasibility of the commercialization of OLEV.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1826-1829
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• 2003

Fine chemical production must assure high-standard product quality as well as characterized as multi-product production in small volumes. Installing high-precision batch distillation is one of the common elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. In this study, we investigate the optimal operation strategy and production planning of a sequential multi-purpose plants consisting of batch processes and batch distillation with unlimited intermediate storage. We formulated this problem as an MILP model. A mixed-integer linear programming model is developed based on the time slot, which is used to determine the production sequence and the production path of each batch. Illustrative examples show the effectiveness of the approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.47-58
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• 1988

The dynamic uncapacitated facility location model is formulated by a mixed integer programming. It has the objective of minimizing total discounted costs for meeting demands specified in different time periods at various demand centers. Costs include those for operation of facilities to demand centers and a fixed cost associated with the capital investment. The problem is decomposed into two simple Lagrangian relaxed subproblems which are coordinated by Lagrangian multipliers. We explored the effect of using the subgradient optimization procedure and a viable solution approach is proposed. Computational results are presented and further research directions are discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.708-717
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• 2009

Recently, Korea government decided to introduce RPS (Renewable Portfolio Standard) mechanism which requires electricity providers to gradually increase the amount of renewable energy sources such as wind, solar, bioenergy, and geothermal. As a consequence, it is expected that the long-term fuel mix would be changed to result in more expensive production and the increased production costs would be distributed to the rate payers via electricity tariffs. This paper presents the change in long-term fuel mix in year 2020 with the four RPS scenarios of 3%, 5%, 10% and 20%, and the methodologies for collecting the increased production costs through new tariff schedule. The studies on long-term fuel mix have been carried out with the GATE-PRO (Generation And Transmission Expansion Program) optimization package, a mixed-integer program developed by the Korea Energy Economics Institute and Hongik university. Three methodologies for distributing the production costs to the rate payers have also been demonstrated.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.429-436
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• 2008

In this paper, we study an optimization which determines the optimal sensing time and the number of cooperative sensing cognitive users for cooperative spectrum sensing scheme in cognitive radio networks. In cooperative spectrum sensing, cognitive users originally in inactive status are activated and take part in spectrum sensing along with transmitting cognitive users resulting in a reduced sensing time. Tradeoff between transmission rate gain and energy consumption due to cooperative sensing is formulated as a mixed integer programming problem which is solved for the optimal values.