• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2008.10a
• /
• pp.299-303
• /
• 2008

In this paper, we discuss the schedule problems for Korean Professional Baseball League (KPBL) and propose approaches to solve these problems by applying Integer Programming. A schedule in a sport league must satisfy lots of constraints on timing such as organizational, attractiveness, and fairness requirements. Organizational requirements cover a set of rules which have to guarantee that all the games can be scheduled according to the regulations imposed by Korean Baseball Organization (KBO). Attractiveness requirements focus on what stadium visitors, television spectators, and the clubs expect, that is, a varied, eventful, and exciting season. Fairness requirements have to guarantee that no team is handicapped or favored in comparison with the others. In addition to finding a feasible schedule that meets all the constraints, the problem addressed in this paper has the additional complexity of having the objective of minimizing the travel costs and every team has the balancing number of the games in home. We formalize the KPBL problem into an optimization problem and adopt the concept of evolution strategy to solve it. Using the method proposed, it is efficient to find better results than approaches developed before.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2007.05a
• /
• pp.328-333
• /
• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Proceedings of the KIEE Conference
• /
• 2006.11a
• /
• pp.357-359
• /
• 2006

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.365-370
• /
• 2001

The genetic algorithm that simulates the virus evolutionary theory has been developed applying to combinatorial optimization problems. The algorithm in this study uses only one individual and a population of viruses. The individual is attacked, inflected and improved by the viruses. The viruses are composed of flour genes (a pair of top gene and a pair of tail gene). If the individual is improved by the attacking, the inflection occurs. After the infection, the tail genes are mutated. If the same virus attacks several times and fails to inflect, the top genes of the virus are mutated. By this mutation, the individual can be improved effectively. In addition, the influence of the immunologic mechanism on evolution is simulated.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.12
• /
• pp.603-610
• /
• 2002

In this paper, a new economic dispatch algorithm for unit commitment is proposed to improve both the accuracy of the final solution and the calculation speed of economic dispatch. By using the inverse incremental cost functions, economic dispatch can be transformed into a simple optimization problem associated with an n-th order polynomial equation. The proposed method remarkably reduces the computation time with adaptability to any higher order generation cost functions. The proposed method is tested with sample system, which shows that the proposed algorithm yields more accurate and economical generation scheduling results with high computation speed.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.135-137
• /
• 2009

Mathematical models for describing the Human Immunodeficiency Virus(HIV) infection can be devised to better understand how the HIV causes Acquired Immune Deficiency Syndrome(AIDS). The HIV models can then be used to find clues to curing AIDS from a control theoretical point of view. Some models take Cytotoxic T Lymphocytes(CTL) response to HIV infection into account, and others consider mutants against the drugs. However, to the best of our knowledge, there has been no model developed, which describes CTL response and mutant HIV together. Hence we propose a unified model to consider both of these. On the basis of the resulting model, we also present a Model Predictive Control(MPC) scheme to find an optimal treatment strategy. The optimization is performed under the assumption that the Structured Treatment Interruption(STI) policy is employed.

• Journal of applied mathematics & informatics
• /
• v.26 no.5_6
• /
• pp.1021-1035
• /
• 2008

In this paper, we analyze an N-design call center with skill-based routing, in which one pool of agents handles two types of calls and another pool of agents handles only one type of calls. The approximate analysis is motivated by a computational complexity that has been observed in the direct stochastic approach and numerical method for finding performance measures. The workforce staffing policy is very important to the successful management of call centers. So the allocation scheduling of the agents can be considered as the optimization problem of the corresponding queueing system to the call center. We use a decomposition algorithm which divides the state space of the queueing system into the subspaces for the approximate analysis of the N-design call center with two different types of agents. We also represent some numerical examples and show the impact of the system parameters on the performance measures.

• Proceedings of the KSPS conference
• /
• 2007.05a
• /
• pp.327-329
• /
• 2007

This paper presents a FSN-based LVCSR system and it's application to the speech TV program guide. Unlike the most popular statistical language model-based system, we used FSN grammar based on the graph theory-based FSN optimization algorithm and knowledge-based advanced word boundary modeling. For the memory and latency efficiency, we implemented the dynamic pruning scheduling based on the histogram of active words and their likelihood distribution. We achieved a 10.7% word accuracy improvement with 57.3% speedup.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.1166-1170
• /
• 2010

In the case of railway freight, there's a lot of process at railway freight terminal. In these days, for operation efficiency improvement, Load/Unload planning is being carried out research. Load/unload problem can be classified as track assignment, container assignment, yard truck route problem, unload equipment scheduling, container yard plan. In this paper, we focus on track assignment and container assignment among the load/unload problem. we analysis information architecture to solve this problem. And we compares two precesses for existing method and optimization method of track/container assignment processes. An contents different analysis of two methods can shows reformation of an information architecture for load/unload process in the railway freight terminal.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.514-518
• /
• 1990

This paper describes an experimental Knowledge-Based Control System, named KBCS, for manufacturing and assembly. The KBCS of five parts and function : data-base, knowledge acquisition, optimization, and graphic monitoring. The KBCS is utilized for a FMS which is of five machine centers and automatic assembly lines. Each machine can perform almost all manufacturing functions which some difference in efficiency. Buffers store temporarily the incoming components and the outing components. Parts arrive at assembly lines after many steps of manufacturing, and the transfer path and time are determined by procedural knowledge of control systems. Nine different incoming components are set up. The total control system is expected to perform four algorithms, timing algorithm ,sequencing algorithm, penalty algorithm, and cart algorithm. The construction of controller require basic components of manufacturing systems in which knowledges are formulated on the base of the results and the repeated simulation of KBCS with graphic monitoring system. Simulation results by KBCS are compared with those by the other rules of manufacturing.