• KIEE International Transactions on Power Engineering
• /
• v.5A no.4
• /
• pp.331-338
• /
• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.4
• /
• pp.187-198
• /
• 2022

This paper addresses the maintenance optimization problem in multi-component systems in which parts are connected in series, carrying out several missions interspersed with scheduled finite breaks. Due to limited time or resources, maintenance actions can be only carried out on a limited set of components. The decision maker then has to decide which components to maintain to ensure a pre-specified performance level during next mission. Most of the existing models in the literature usually assume only one system and enough spare parts. However, there are situations in which maintenance is required for multiple systems of the same type. To overcome this restrictive assumption, this study optimizes the maintenance problem considering the lack of repair parts and cannibalism for many identical systems. This study presents two optimization models with different objectives to solve the problem and analyzes the results so that the decision maker can decide. The results of this study are expected to be used for the maintenance of multiple systems of the same type, such as swarm drones.

• Journal of Korean Institute of Industrial Engineers
• /
• v.34 no.3
• /
• pp.318-327
• /
• 2008

This paper considers a single-machine scheduling problem with availability constraints. In many realistic situations, machines may not be always available due to various reasons such as maintenance, breakdown and repair. However, most literature on scheduling assume that the machines are available at all times. This paper deals with a single-machine scheduling problem with periodic maintenance. If the maintenance decision is made jointly with the job scheduling, the system will be more effective. The objective is to minimize the total completion time of jobs. This problem is proved to be NP-hard in the strong sense. The proposed breaking heuristic(BH) algorithm rule is established by some theorems and conditions. Our computational results show that the BH algorithm is much more efficient than existing heuristic.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.826-828
• /
• 1996

Genetic Algorithm(GA) is a searching or optimizing algorithm based on natural evolution principle. GA has demonstrated considerable success in providing good solutions to many nonlinear, multi-dimensional optimization problems. The preventative maintenance scheduling is a kind of dynamic optimization problem with constraints. This paper applies GA to the preventative maintenance scheduling problem. In the case study, we can get the preventative maintenance scheduling of 3-generators during 8 weeks using GA. It is shown that GA can be available to the preventative maintenance scheduling problem.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.5 no.4
• /
• pp.161-167
• /
• 2001

By means of analyzing the problems in monitoring plan, design, installation, operation based on maintenance monitoring system installed in subway tunnel section, the improved methods of were proposed for applying to subway monitoring maintenance effectively in the future. The choice of the better monitoring system, the operating method of monitoring system, the confidence and continuity of maintenance monitoring, the performance of responsible monitoring supervision in the phase of the planning of monitoring and design were proposed. The problem and developed plan in the different monitoring systems, the calibration and correction of monitoring system, the analysis for the results and plan for maintenance in the phase of installation of monitoring system and operation were also proposed.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.5
• /
• pp.545-552
• /
• 1999

The Maintenance scheduling is one of the mid-term scheduling problems systems. There have been many methods for this problem, but there is no effective way to treat all the generators simultaneously. In this paper, we apply a genetic algorithm(GA) to the maintenance scheduling problem. We proposed new crossover operators(BOX type crossover) to improve searching ability of GA. Satisfactory results are obtained by GA with the proposed corssover operators.

• Proceedings of the KIEE Conference
• /
• 2006.11a
• /
• pp.222-224
• /
• 2006

This paper addresses a particle swarm optimization-based approach for solving a generating unit maintenance scheduling problem(GMS) with some constraints. We focus on the power system reliability such as reserve ratio better than cost function as the objective function of GMS problem. It is shown that particle swarm optimization-based method is effective in obtaining feasible schedules such as GMS problem related to power system planning and operation. In this paper, we find the optimal solution of the GMS problem within a specific time horizon using particle swarm optimization algorithm. Simple case study with 16-generators system is applicable to the GMS problem. From the result, we can conclude that PSO is enough to look for the optimal solution properly in the generating unit maintenance scheduling problem.

• Journal of the Korean Society for Railway
• /
• v.14 no.3
• /
• pp.216-221
• /
• 2011

An important problem in reliability analysis for repairable systems is to model the maintenance effect. The most of researches have assumed two extreme cases; one is perfect maintenance and the other is minimal maintenance. However, many of maintenances performed by domestic subway operators are imperfect maintenances which have the effect between both of two extreme cases. This article deals with the problem determining the imperfect preventive maintenance intervals based on failure data in units of the PDS(passenger door system) in Metro EMU. This paper deals with a case study on determining imperfect maintenance interval by using the level of maintenance effect through reliability analysis of PDS.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2000.03c
• /
• pp.93-104
• /
• 2000

By means of analyzing the problems in monitoring plan, design, installation, operation based on maintenance monitoring system installed in subway tunnel section, the methods of improvement were proposed for applying to subway monitoring maintenance effectively in future. The choice of the better monitoring system, the operating method of monitoring system, the confidence and continuity of maintenance monitoring, the performance of responsible monitoring supervision in the phase of the planning of monitoring and design were proposed. The problem and developed plan in the different monitoring systems, the calibration and correction of monitoring system, the analysis for the results and plan for maintenance in the phase of installation of monitoring system and operation were also proposed.

• Journal of Fisheries and Marine Sciences Education
• /
• v.27 no.3
• /
• pp.841-852
• /
• 2015

The objectives of this study are to amend of the Small Stream Maintenance Act. In general, small streams have diverse ecological and social characteristics because they are extensively formed across watersheds over time. However, small streams in Korea have been significantly degraded primarily because of human disturbances including stream maintenance activities. Especially, covered streams are majority problem in the Small Stream Maintenance. In order to improve this problem, the Small Stream Maintenance Act be amended to the Small Stream Management Act.