• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1088-1095
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• 1999

This paper presents short-term hydro scheduling method for hydrothermal coordination by genetic algorithms. Hydro scheduling problem has many constraints with fixed final reservoir volume. In this paper, the difficult water balance constraints caused by hydraulic coupling satisfied throughout dynamic decoding method. Adaptive penalizing method was also proposed to handle the infeasible solutions that violate various constraints. In this paper, we proposed GA to solve hydrothermal scheduling with appropriate decoding method and dynamic penalty method. The effectiveness of the proposed method is demonstrated in the case study.

• ETRI Journal
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• 제29권2호
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• pp.201-211
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• 2007

This paper focuses on the scheduling problem with the objective of maximizing system throughput, while guaranteeing long-term quality of service (QoS) constraints for non-realtime data users and short-term QoS constraints for realtime multimedia users in multiclass service high-speed uplink packet access (HSUPA) systems. After studying the feasible rate region for multiclass service HSUPA systems, we formulate this scheduling problem and propose a multi-constraints HSUPA opportunistic scheduling (MHOS) algorithm to solve this problem. The MHOS algorithm selects the optimal subset of users for transmission at each time slot to maximize system throughput, while guaranteeing the different constraints. The selection is made according to channel condition, feasible rate region, and user weights, which are adjusted by stochastic approximation algorithms to guarantee the different QoS constraints at different time scales. Simulation results show that the proposed MHOS algorithm guarantees QoS constraints, and achieves high system throughput.

• 지능정보연구
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• 제12권4호
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• pp.39-51
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• 2006

선사에서 화물을 수송하기 위해 필요한 공(빈) 컨테이너 수요를 만족시키기 위해서 컨테이너를 구매하고 임대하는 계획을 작성하는 방법에 대해서 다루었다. 수요의 변동을 고려하여 각 기간별로 구매 또는 임대하여야 할 컨테이너의 개수와 임대기간을 결정하는 방법을 제시하였다. 컨테이너 구매 및 임대 계획작성을 위한 확정적 수리계획 모형을 제안하였으며 이 모형의 해를 구하기 위한 발견적 기법을 제안하였다.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1882-1890
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• 2014

This paper proposes an augmented Lagrange Hopfield network (ALHN) based method for solving multi-objective short term fixed head hydrothermal scheduling problem. The main objective of the problem is to minimize both total power generation cost and emissions of $NO_x$, $SO_2$, and $CO_2$ over a scheduling period of one day while satisfying power balance, hydraulic, and generator operating limits constraints. The ALHN method is a combination of augmented Lagrange relaxation and continuous Hopfield neural network where the augmented Lagrange function is directly used as the energy function of the network. For implementation of the ALHN based method for solving the problem, ALHN is implemented for obtaining non-dominated solutions and fuzzy set theory is applied for obtaining the best compromise solution. The proposed method has been tested on different systems with different analyses and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is very efficient for solving the problem with good optimal solution and fast computational time. Therefore, the proposed ALHN can be a very favorable method for solving the multi-objective short term fixed head hydrothermal scheduling problems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.289-291
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• 1998

This paper presents short-term hydro scheduling method for hydrothermal coordination by genetic algorithm. Hydro scheduling problem has many constraints with fixed final reservoir volume. In this paper, the difficult water balance constraints caused by hydraulic coupling satisfied throughout dynamic decoding method. Adaptive penalizing method was also proposed to handle the infeasible solutions that violate various constraints. The effectiveness of proposed method in this paper was examined through the case studies. Further studies for the validation of the hydro scheduling scheme obtained by genetic algorithm will be very appreciated.

• 한국시뮬레이션학회논문지
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• 제19권1호
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• pp.73-82
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• 2010

전 세계 조선 산업에서 생산성의 향상이 크게 이슈화되면서, 생산 라인의 생산성 향상을 위해 새로운 방법론, 생산 자동화, 향상된 생산계획 및 일정계획 등의 연구가 진행되어 왔다. 본 연구는 조선 생산의 일정계획과 관련하여 소조립 라인의 소일정계획의 최적화를 통한 생산성 향상에 관한 것이다. 소조립 라인의 소일정계획 최적화를 위하여 공정 별 작업자 배치와 운용에 관한 시나리오와 스키드 패턴의 투입 순서를 미정 다항식 문제로 정식화하고 문제 해결하기 위해 메타휴리스틱 방법 중 하나이며 확률변수를 사용하는 시뮬레이티드 어닐링을 적용하여 지역 최소값에 빠지는 것을 막고 전역 최소값을 찾도록 하였다. 실제 조선소의 소조립 라인의 작업 시간 데이터와 스키드 투입 순서 데이터를 사용하여 최적화를 수행하고 최적화 결과의 효과를 검증하였다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.1940-1949
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• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.370-375
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• 1992

This paper deals with the scheduling and simulation for FMC(Flexible Manufacturing Cells). In order to achieve CIM, there is a critical need to link factory level and machine level. The primary functions performed by this link for all jobs issued to the shop floor and cell include short-term scheduling and dynamic operational scheduling. Here, hierarchical control structure is introduced to define these functions. And Intelligent scheduling through expert module is adopted for efficiency of FMC operation. Computer simulation reveals that expert scheduling method is better than heuristics in various performance index.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 춘계학술대회 논문집
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• pp.280-285
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• 2003

The process of railway traffic planning is composed of several steps such as long-term, mid-term. short-term, and real-time plan. The planning of vehicle and manpower resources is a main research topic in tactical short-term planning step. Railway vehicle is usually consisted of a power car, passenger/freight cars and human resource is composed of engine driver, cabin crew, ground personnel. So far, power car was main research target in railway vehicle scheduling problem. Recently according as the light electric railway or high-speed railway is introduced, the operational planning of trainset vehicles become important, In this paper, we introduce the conceptional model for trainset restoring problem and developed heuristic algorithm.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2003년도 춘계학술대회
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• pp.53-61
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• 2003

The process of railway traffic planning is composed of several steps such as long - term, mid - term, short - term, and real - time plan. The planning of vehicle and manpower resources is a main research topic in tactical short - term planning step Railway vehicle is usually consisted of a power car, passenger/freight cars and human resource is composed of engine driver, cabin crew, ground personnel. So far , power car was main research target in railway vehicle scheduling problem. Recently according as the light electric railway or high - speed railway is introduced, the operational planning of train set vehicles become important . In this paper , we introduce the conceptional model for trainset restoring problem and developed heuristic algorithm.