• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.666-669
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• 2002

A microprocessor with genetic instructions such as crossover, mutation and inversion is proposed. The processor is modeled using VHDL, synthesized to a schematic and implemented on a FPGA. The control path is implemented with a microprogram consisting of about 15032-bit microwords, and the operation of each instruction is checked through simulation.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.203-208
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• 2002

In case of the problems with multiple plants, alternative operation sequence, alternative machine, setup time, and transportation time between plants, we need a robust methodology for the integration of process planning and scheduling in supply chain. The objective of this model is to minimize the tardiness and to maximize the resource utilization. So, we propose a multi-objective model with limited-capacity constraint. To solve this model, we develope an efficient and flexible model using adaptive genetic algorithm(AGA), compared to traditional genetic algorithm(TGA)

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.165-167
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• 2007

This paper presents a analysis method for power system stability using a Modified Genetic-based Power System Stabilized(MGPSS). The proposed MGPSS parameters are optimized using Modified Genetic Algorithm(MGA) in order to maintain optimal operation of generator under the various operating conditions. To improve the convergence characteristics, real variable string is adopted. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performance than conventional controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.938-941
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• 1995

This paper is concerned with the determination of assembly unit for hull block assembly processes for shipbuilding. In this study,genetic algorithm is adopted for assembly level allocation and assemaly unit is determined by rule-based reasoning. The criteria to detemine assembly unit is to minimize welding operation time for the block assembly.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.786-798
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• 2007

As we go about our daily lives, people often collect surrounding information and adapt to the situation. Computer development trends show that one wants computers to work like human beings, i.e. computers can sense its context and adapt corresponding to context changes. To implement this expectation, a context aware service layer is needed. In this layer, sensors capture its environment and send this information to the service center. Considering received information as its context, the service center seeks the suitable operation according to the context. Tills paper presents a context aware service which is applied in controlling air-conditioner. The air-conditioner includes sensors which are installed at some special positions in a room. Each of these sensors gathers comfort-influenced information like temperature, humidity and sends them to air-conditioner. The air-conditioner adapts its operation to the environment according to the sensed information. To control the air-conditioner effectively, we use a genetic algorithm which is suitable in adaptation issues. The simulation shows that the room condition can be maintained at a comfortable level by using context-aware services in the operation of the air-conditioning system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.7
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• pp.299-304
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• 2016

In recent years, heat source systems which have a principal effect on the performance of buildings are difficult to design optimally as a great number of design factors and constraints in large and complicated buildings need to be considered. On the other hand, it is necessary to design an optimum system combination and operation planning for energy efficiency considering Life Cycle Cost (LCC). This study suggests a multi-level and multi-objective optimization method to minimize both LCC and investment cost using a genetic algorithm targeting an office building which requires a large cooling load. The optimum method uses a two stage process to derive the system combination and the operation schedule by utilizing the input data of cooling and heating load profile and system performance characteristics calculated by dynamic energy simulation. The results were assessed by Pareto analysis and a number of Pareto optimal solutions were determined. Moreover, it was confirmed that the derived operation schedule was useful for operating the heat source systems efficiently against the building energy requirements. Consequently, the proposed optimization method is determined by a valid way if the design process is difficult to optimize.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.390-399
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• 2011

Generally the life-cycle cost of complex systems composed of several sub systems or equipments such as train, aircraft weapon systems is spent much more during operation and maintenance phase than development phase. The maintenance cost for maintaining the availability and extending the life span of systems comprise a large proportion of systems operation cost. The cycle of preventive maintenance affects operation and maintenance cost a lot. In this study we introduce a way minimizing life-cycle cost of systems by calculating more reliable preventive maintenance period than the results of previous study using systems reliability data considered the reliability and failure effect ratio of sub-systems or components. We can solve the preventive maintenance period problem known as NP-Hard as quick as possible by using modified genetic algorithm than using other models introduced in previous study.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.17-29
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• 2017

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.949-963
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• 2017

This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.