• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.329-337
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• 2016

With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.363-365
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• 1991

This paper presents a method for feeder reconfiguration in order to operate distribution systems efficiently using heuristic rules. The reconfiguration method presented here not only eliminates various abnormal states but also achieves minimum power loss and optimum load balance of the distribution feeders under normal operating condition transfering loads from one feeder to anoter applying the experiences of the experts. To implement the method effectively, a best-first tree searching strategy based on heuristics is used to evaluate the various load transfer alternatives. The development of a rule-based system aimed at the reduction of the search space is presented as a means of implementing the best-first searching strategy. The results of the computer simulation of the above procedure are as follows; 1) achieving minimum power loss of the distribution feeder adopting the optimum load transfer alternative. 2) Enhencing system reliability and achieving load balance through rational allocation of the feeder loads.

• 전기학회논문지
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• 제58권9호
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• pp.1681-1688
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• 2009

This paper proposes a new fault restoration method which adopts the recloser as top agent to release the problems of the data concentration and fault processing delay of the existing DAS(distribution Automation System) under the ubiquitous distribution system. In proposed method, top agent collects the data based on the multi-casting communication with the tie switches of the interconnection point, and then selects a closed switch(tie switch) to transfer the sound outage load to other feeders based on the heuristic search strategy step by step until the load transfer work is finished. Here, a new heuristic rule is developed which can guarantee the relational load balancing and line loss from the collected voltage data. Finally, the several faults are simulated for typical multi-section and multi-interconnection distribution system to prove the effectiveness of the proposed strategy, in particular, for each simulation cases, the load balancing index and line loss index of the obtained solution from the proposed method is compared with those of all of feasible solutions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• 산업경영시스템학회지
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• 제46권4호
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• pp.238-245
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• 2023

As technologies have been more quickly developed in this 4th Industry Revolution era, their application to defense industry has been also growing. With these much advanced technologies, we attempt to use Manned-Unmanned Teaming systems in various military operations. In this study, we consider the Location-Routing Problem for reconnaissance surveillance missions of the maritime manned-unmanned surface vehicles. As a solution technique, the two-phase method is presented. In the first location phase, the p-median problem is solved to determine which nodes are used as the seeds for the manned vehicles using Lagrangian relaxation with the subgradient method. In the second routing phase, using the results obtained from the location phase, the Vehicle Routing Problems are solved to determine the search routes of the unmanned vehicles by applying the Location Based Heuristic. For three network data sets, computational experiments are conducted to show the performance of the proposed two-phase method.

• Nuclear Engineering and Technology
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• 제25권2호
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• pp.193-203
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• 1993

재장전노심의 핵연료 장전모형 설계를 위한 기존의 알고리즘 탐색방법의 단점을 보완하기 위한 새로운 경험적 탐색방법을 개발하였다. 노심의 핵연료 장전모형으로 고려될 수 있는 수없이 많은 경우의 수를 줄이기 위하여 일반적 핵연료 배치규칙, 영역별 배치방법 그리고 장전모형의 집단화 방법을 이용하였다. 비슷한 장전모형을 모아서 집단화시키는 기준으로 엔트로피 이론을 이용하였다. 또한 PROLOG언어를 이용하여 주어진 배치규칙에 따라 장전모형을 탐색하는 프로그램을 만들었다. 장전모형들의 노심내 출력분포 해석에는 2군 nodal코드인 MEDIUM-2D를 사용하였다. 이와같은 방법을 사용한 결과 수백개 정도의 장전모형 집단을 찾아낼 수 있었고, 여기에 가연성 독봉 배치규칙에 따라 가연성 독봉을 배치한 결과 장전모형 집단의 수를 수십개까지로 감소시킬 수 있었다. 이러한 장전모형 집단들로부터 실제로 이용 가능한 장전모형을 찾아내기 위하여, 주기길이 최대화방법과 첨두 출력 최소화방법을 사용하였다. 그 결과 고리 3호기 제10주기의 예상 재장전모형보다 주기길이는 길고 첨두출력은 낮은 장전모형을 찾아낼 수 있었다.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.403-416
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• 2013

This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.258-258
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• 2012

In frequency analyses of hydrological data, it is necessary for the interested variables to be homogenous and independent. However, recent evidences have shown that the occurrence of extreme hydro-meteorological events is influenced by large-scale climate variability, and the assumption of homogeneity does not generally hold anymore. Therefore, in order to associate the non-homogenous characteristics of hydro-meteorological variables, we propose the parameter estimation method of probability models using meta-heuristic algorithms, specifically harmony search. All the weather stations in South Korea were employed to demonstrate the performance of the proposed approaches. The results showed that the proposed parameter estimation method using harmony search is a comparativealternative for the probability distribution of the non-homogenous hydro-meteorological variables data.

• 한국경영과학회지
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• 제23권2호
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• pp.83-101
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• 1998

Assembly U-lines are increasingly accepted in industry, especially just-in-time production systems, for the efficient utilization of workforce. In this paper, we present an integer programming formulation and a branch-and-bound method for balancing the U-line with the objective of minimizing the number of workstations with a fixed cycle time. In the mathematical model, we provide the method that can reduce the number of variables and constraints. The proposed branch-and-bound method searches the optimal solution based on a depth-first-search. To efficiently search for the optimal solutions to the problems, an assignment rule is used in the method. Bounding strategies and dominance rules are also utilized. Some problems require a large amount of computation time to find the optimal solutions. For this reason. some heuristic fathoming rules are also proposed. Extensive experiments with test-bed problems in the literature are carried out to show the performance of the proposed method. The computational results show that our method is promising in solution quality.