• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.145-145
• /
• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.1
• /
• pp.1-10
• /
• 2010

Recently, a shipyard is making every effort to efficiently manage equipments of resources such as a gantry crane, transporter, and so on. So far block lifting scheduling of a gantry crane has been manually performed by a manager of the shipyard, and thus it took much time to get scheduling results and moreover the quality of them was not optimal. To improve this, a block lifting scheduling system of the gantry crane using optimization techniques was developed in this study. First, a block lifting scheduling problem was mathematically formulated as a multi-objective optimization problem, considering the minimization of travel distance at an idle state and wire replacement during block lifting. Then, to solve the problem, a meta-heuristic optimization algorithm based on the genetic algorithm was proposed. To evaluate the efficiency and applicability of the developed system, it was applied to an actual block lifting scheduling problem of the shipyard. The result shows that blocks can be efficiently lifted by the gantry crane using the developed system, compared to manual scheduling by a manager.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.157.3-157
• /
• 2001

In this paper, the optimal maintenance scheduling for turbine with considering maintenance replacement rate was proposed in order to reduce the maintenance cost during the whole period of operation, meanwhile keeping current reliability of turbine. The proposed method is only based on a few limited available data with various factors relating to maintenance replacement and repair of turbine. The proposed method will be adopted by Kyushu Electric Power Co., Inc. from April in 2002 to determine the maintenance schedule of thermal power plants.

• Water Engineering Research
• /
• v.3 no.1
• /
• pp.63-74
• /
• 2002

• Journal of the Korean Institute of Navigation
• /
• v.24 no.5
• /
• pp.361-371
• /
• 2000

This paper treats a genetic algorithm for ship scheduling problem in set packing formulation. We newly devised a partition based representation of solution and compose initial population using a domain knowledge of problem which results in saving calculation cost. We established replacement strategy which makes each individual not to degenerate during evolutionary process and applied adaptive mutate operator to improve feasibility of individual. If offspring is feasible then an improve operator is applied to increase objective value without loss of feasibility. A computational experiment was carried out with real data and showed a useful result for a large size real world problem.

• Transactions on Electrical and Electronic Materials
• /
• v.7 no.5
• /
• pp.217-223
• /
• 2006

When only partial information is available about equipment failures (installation date and amount, as well as failure and replacement rates), data on sufficiently large number of yearly populations of the components can be combined, and estimation of model parameters may be possible. The parametric models may then be used for forecasting of the system's short term future failure and for formulation of replacement strategies. We employ the Weibull distribution and show how we estimate its parameters from past failure data. Using Monte Carlo simulations, it is possible to assess confidence ranges of the forecasted component performance data.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.28 no.3
• /
• pp.183-192
• /
• 2022

With the growth of the packaging industry, demand on the packaging printing comes in various forms. Customers' orders are diversifying and the standards for quality are increasing. Offset printing is mainly used in the packaging printing since it is easy to print in large quantities. However, productivity of the offset printing decreases when printing various order. This is because it takes time to change colors for each printing unit. Therefore, scheduling that minimizes the color replacement time and shortens the overall makespan is required. By the existing manual method based on workers' experience or intuition, scheduling results may vary for workers and this uncertainty increase the production cost. In this study, we propose an automated scheduling method of parallel offset printing process for packaging printing. We decompose the original problem into assigning and sequencing orders, and ink arrangement for printing problems. Vehicle routing problem and assignment problem are applied to each part. Mixed integer programming is used to model the problem mathematically. But it needs a lot of computational time to solve as the size of the problem grows. So guided local search algorithm is used to solve the problem. Through actual data experiments, we reviewed our method's applicability and role in the field.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1991.10a
• /
• pp.147-159
• /
• 1991

Stochastic convexity(concvity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through the probabilistic construction based on the sample path approach. A Markov additive process is obtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or for optimal operation schedule of a wide range of stochastic systems. We also clarify the conditions for stochatic monotonicity of the Markov process, which is required for stochatic convexity of the Markov additive process. This result shows that stochastic convexity can be used for the analysis of probabilistic models based on birth and death processes, which have very wide application area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.16 no.1
• /
• pp.76-88
• /
• 1991

Stochastic convexity (concavity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through probabilistic construction based on the sample path approach. A Markov additive process is abtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or optimal operation schedule wide range of stochastic systems. We also clarify the conditions for stochastic monotonicity of the Markov process. From the result it is shown that stachstic convexity can be used for the analysis of probabilitic models based on birth and death processes, which have very wide applications area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2013.06a
• /
• pp.60-61
• /
• 2013

One of the most important indicators for measuring service level and productivity of the port may be a demurrage rate. Currently, in the case of grain terminal of Busan North Port, demurrage rate are recognized at a very high level, in order to improve this, it is tilted more effort operational. In order to reduce the demurrage, there is a way expansion of facility of hardware, such as the replacement of aging equipment, and how manipulative assignment rules of the apparatus of the operation on the software side, such as changing the order of facility allocation. If the financial reasons are out of question, it is possible to expand to reduce the demurrage rate by operational way. Therefore this paper deals with how to operate some of the allocation rules and silo allocation rules of equipment to reduce the work hours with model and how to operate basic equipment and grain terminal of Busan North Port want to be seen by comparative analysis.