• 한국통신학회논문지
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• 제27권11C호
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• pp.1132-1138
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• 2002

본 논문은 시간 제약 조건하에서의 최적 선택 공급 전압을 위한 전력 감소 스케줄링 알고리듬을 제안한다. 전력감소 스케줄링에서는 전력소비를 줄이기 위해 가변 전압 레벨을 이용해 최적 공급 전압을 선택 휴리스틱 방법으로 연산을 수행하여 제어 스텝을 결정한다. 그리고 최적 선택 공급 전압 바인딩에서는 그래프 컬러링 기법을 이용해 레지스터 상의 전력 소비의 주원인인 스위칭 활동을 최소화한다. 상위 수준 벤치마크 예제를 이용한 실험으로부터 우리는 최적 선택 공급 전압을 이용한 제안한 알고리듬이 획일화된 단일 전압을 이용한 알고리듬보다 전력 소비를 줄이는데 효율적임을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3496-3514
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• 2015

One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.531-534
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• 2001

프로젝트 초기단계에 공기산정이 적절히 이루어져야만 프로젝트 진행과정에서 인력, 자재, 장비 등을 효율적으로 이용할 수 있으며 자금을 적절하게 배분할 수 있다. 그러나 아직 국내에서는 기준으로 삼을 만한 공기산정 기준이 없는 실정이다. 본 연구에서는 현재의 불명확한 공기산정방식을 개선함으로써 프로젝트 초기단계에서 적정공기를 예측하고 타당한 공정계획을 수립할 수 있도록 합리적이고 체계적인 공기 산정기준을 제시하고자 한다. 이를 위하여 본 연구에서는 기존 산정기준의 비교 분석을 통하여 개선방향을 도출하고, 현장기술자들과의 면담조사, 현장실험, 기존 연구자료 등을 활용하여 적정공기 산정기준을 제시하였다.

• 산업경영시스템학회지
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• 제5권7호
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• pp.9-15
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• 1982

The rectilinear-distance location problem combines the property of being a very appropriate distance measure for a large number of location problems and the property of being very simple to treat analytically. An obvious question to be asked at the optimal point which is obtained by the rectilinear distance method is, "what if the point is not available as a location site\ulcorner." The point may, for example, be inaccessible or may coincide with the location of another structure, a river, or a municipal park. In this case, one approach that may be employed is to construct contour lines (also called iso-cost or level curves) of the cost function. Contour lines provide considerable insight into the shape of the surface of the total cost function as well as a useful means of evaluating alternative locations for the new facility. But, when there is an obstacle which divides the application area into two. The optimal location(which is acquired by the rectilinear distance method) is not coincide with the minimal cost point and the contour line is occasionally of no use, this paper shows the method of finding a way to decide an optimal point of single facility location in this case.this case.

• 전자공학회논문지S
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• 제35S권4호
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.559-561
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• 1995

The cogeneration system has a strong merit in providing thermal and electrical energy simultaneously. Nowadays, cogeneration system is widely used in the point of efficient use of the energy resources And the installation of the system is expected to be greatly increased in each year. So, we need to develop an optimal operation planning for those systems. In this paper, we are used to result what studed at the my power system of room because it is in order to solve maintenance scheduling problem. Also we added a constraints to the proposed maintenance model for optimal maintenance rate. In the case study, we construct an multi-machine generated example system which operated in topping cycle, and calculate the yearly optimal production cost, marginal maintenance cost, and maintenance scheduling of the example system respectively.

• 설비공학논문집
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• 제26권2호
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• pp.86-90
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• 2014

It is important to select an optimal capacity for equipment, because the initial cost of new and renewable energy system is more expensive than that of exiting system. An optimal equipment and enhanced rate of operation can be selected, to analyze the cooling and heating load of buildings. In this study, seawater heat pump system in the Jeju area will be applied, by the heat source equipment of district heating. The loads of buildings are analyzed from existing researches, to select optimal capacity of equipment. Also, an optimal rate of building use will be set up, from a combination of buildings.

• 산업경영시스템학회지
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• 제14권24호
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• pp.123-132
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• 1991

This study deals with the experiment of perceiving visual information according to the positions of vehicle side mirrors. In the design of vehicle, the consideration of safety is very important. Therefore we consider the positions of side mirrors to use visual information effectively which is important factor to driver. This paper presents the position of side mirror to elevate the degree of visual perception for the circumstances of danger by experiments. To exhibit the circumstances of danger. 4 LED(Light Emitted Diode) art located at each side(right. left front. hack) of vehicle. A subject pushes the LED switch to see that if he perceives the circumstance of danger. To record the circumstance of randomly generated danger, computer interface card is used to control 4 LED and swithch on IBM PC/AT Experiments are divided into 2 parts. The 1st experiment present the independence of right & left side mirror. The 2nd experiment present optimal position of right & left side mirror. The vehicle used in experiment is model EL of H Co.. Statistical process of experimental data using SPSS(Statistical Package for Social Sciences)/PC package concludes that 1) the optimal position of right side mirror is 54cm forward of exist position. 2) for the left side mirror, the position of 120cm forward of exist position shows the worst degree of perception. and the optimal position does not exist in statistical meaning.

• 대한전기학회논문지
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• 제39권3호
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• pp.232-239
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• 1990

A new algorithm is suggested to solve the optimal reactive power and voltage control (optimal VAR control) problem. The model minimizes the real power losses in the system. The constraints include the reactive power limits of the generators, limits on the bus voltages and the operating limits of control variables-the transformer tap positions generator terminal voltages and switchable reactive power sources. The method presented herein, using a newly developed Jacobian decomposition method, employs linearized sensitivity relationships of power systems to establish both the objective function for minimizing the system losses and the system performance sensitivities relating dependent and control variables. The algorithm consists of two modules, i.e. the Q-V module for reactive power-voltage control, and load flow module for computational error adjustments. In particular the acceleration factor technique is introduced to enhance the convergence property in Q-V module. The combined use of the afore-mentioned two modules ensures more effective and efficient solutions for optimal reactive power dispatch problems. Results of the application of the method to a sample system and other worst-case systems demonstrated that the algorithm suggested herein is compared favourably with conventional ones in terms of computation accuracy and convergence characteristics.

• 전기학회논문지
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• 제62권1호
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.