• 한국정보과학회논문지:정보통신
• /
• 제28권4호
• /
• pp.657-664
• /
• 2001

선행 논문(제1부)[13]에서는 광 베니언-형 교환 망에 있어 누화를 야기하는 멀티캐스트 접속들간의 관계를 그래프로 표현하고, 해당 그래프의 차수의 상한을 제시하였다. 본 논문(제2부)에서는 교환소자를 달리하는 멀티캐스팅의 스케줄링에서의 라우팅 횟수 즉, 스케줄링 길이에 대해 다룬다. 최적의 스케줄링 길이를 구하는 문제는 NP-complete이므로 최적 길이의 상한의 두 배 이내의 길이를 제공하는 근사 알고리즘을 제시한다. 아울러, 링크를 달리하는(즉, 넌블럭킹) 멀티캐스팅에 관한 스케줄링 길이를 고찰한다. 얻어진 스케줄링 길이 하에서 다양한 넌블럭킹 베니언-형 멀티캐스팅 망들을 규명한다.

• KIEE International Transactions on Power Engineering
• /
• 제5A권4호
• /
• 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.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 1996년도 The Korean Institute of Navigation 1996년도 춘계학술발표회 논문집
• /
• pp.59-76
• /
• 1996

Vessels in the world merchant fleet generally operate in either liner or bulk trade. The supply and the demand trend of general cargo ship are both on the ebb however those trend of tankers and containers are ins light ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a texbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charter's market. This implies that the proper scheduling of tankers under spot market fluctuation has the great potential of improving the owner's profit and economic performance of shipping. This paper aims at developing the TS-DSS(Decision Support System for Tanker Scheduling) in the context of the importance of scheduling decisions. TS-DSS is defined as a DSS based on the optimization models for tanker scheduling. The system has been developed through the life cycle of systems analysis design and implementation to be user-friendly system. The performance of the system has been tested and examined by using the data edited under several tanker scheduling has been tested and examined by using the data edited under several tanker scheduling scenarios and thereby the effectiveness of TS-DSS is validated satisfactorily. The authors conclude the paper with the comments of the need of appropriate support environment such as data-based DSS and network system for successful implementatio of the TS-DSS.

• 한국ITS학회 논문지
• /
• 제8권1호
• /
• pp.1-8
• /
• 2009

본 연구는 기존의 버스 운영계획모형을 시스템 다이나믹스(System Dynamics : SD) 관점에서 검토하는 것을 주된 목적으로 하고 있다. 결정변수들 간의 선형적 관계에 기초한 교��비용모델에 SD관점을 적용하여 순환적 관계로의 재구성을 시도하였으며, 그 결과물로 최적배차간격모형의 인과지도(Causal Loop Diagram)을 제시하였다. 또한 계량적 시뮬레이션이 가능한 저유량 인과지도(Stock & Flow Diagram)을 작성하여 시뮬레이션 결과의 의미를 논의하였다. 연구결과, 시뮬레이션에 적용한 수식이 기존의 교통비용모형에 토대를 두고 있기 때문에 시뮬레이션 결과가 기존의 연구와 큰 차이를 보이지 않았다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
• /
• pp.319-322
• /
• 1995

As a trend toward multi-product batch processes is increasing in Chemical Process Industry (CPI), multi-product batch scheduling has been actively studied. But the optimal production scheduling problems for multi-product batch processes are known as NP-complete. Recently Ku and Karimi [5] have studied Simulated Annealing(SA) and Jung et al.[6] have developed Modified Simulated Annealing (MSA) method which was composed of two stage search algorithms for scheduling of batch processes with UIS and NIS. Jung et al.[9] also have studied the Common Intermediate Storage(CIS) policy which have accepted as a high efficient intermediate storage policy. It can be also applied to pipeless mobile intermediate storage pacilities. In spite of these above researches, there have been no contribution of scheduling of CIS policy for chemical batch processes. In this paper, we have developed another MSA for scheduling chemical batch processes with searching the suitable control parameters for CIS policy and have tested the this algorithm with randomly generated various scheduling problems. From these tests, MSA is outperformed to general SA for CIS batch process system.

• 제어로봇시스템학회논문지
• /
• 제5권6호
• /
• pp.714-723
• /
• 1999

This paper presents a short-term scheduling algorithm for the operation of steelmaking processes. The scope of the problem covers refining of the hot iron transferred form a blast furnace, ladle treatment, continuous casting, hot-rolling, and coiling for the final products that should satisfy the given demand. The processing time at each unit depends on how much the batch amount is treated, and te dedicated intermediate storage with finite capacity between the units is considered. Resource constraints and initial amount of each state are incorporated into the presented scheduling model for the algorithm of on-line scheduling. We propose amixed integer linear programming (MILP) model with two objectives for the scheduling. The first is to maximize the total profit while atisfying the due date constraint for each product. And the second is to minimize the total processing time, makespan, while satisfying the demand for each product. Especially, we observe the effect of penalizing the intermediate storage and the inventory level of the final product on the scheduling results.

• Journal of Computing Science and Engineering
• /
• 제7권1호
• /
• pp.67-80
• /
• 2013

The worst-case execution time (WCET) of each real-time task in multicore processors with shared caches can be significantly affected by inter-thread cache interferences. The worst-case inter-thread cache interferences are dependent on how tasks are scheduled to run on different cores. Therefore, there is a circular dependence between real-time task scheduling, the worst-case inter-thread cache interferences, and WCET in multicore processors, which is not the case for single-core processors. To address this challenging problem, we present an offline real-time scheduling approach for multicore processors by considering the worst-case inter-thread interferences on shared L2 caches. Our scheduling approach uses a greedy heuristic to generate safe schedules while minimizing the worst-case inter-thread shared L2 cache interferences and WCET. The experimental results demonstrate that the proposed approach can reduce the utilization of the resulting schedule by about 12% on average compared to the cyclic multicore scheduling approaches in our theoretical model. Our evaluation indicates that the enhanced scheduling approach is more likely to generate feasible and safe schedules with stricter timing constraints in multicore real-time systems.

• 한국정보통신학회논문지
• /
• 제15권8호
• /
• pp.1820-1831
• /
• 2011

본 논문에서는 제한된 에너지 자원을 사용하는 센서 노드에서 실시간 및 비실시간 태스크의 실행이 요구되는 경우, 효율적인 전력 소비와 실시간 태스크의 마감시한 보장 및 비실시간 태스크의 향상된 평균 응답 시간을 제공하는 혼합 태스크 스케줄링 기법을 제안하였다. 제안한 혼합 태스크 스케줄링 기법은 기존 EDF 기반 DVS 스케줄링 기법, FIFO 기반 TinyOS 스케줄링 기법과 태스크 클러스터링 기반의 비선점형 실시간 스케줄링 기법과 성능을 비교하여 그 우수성을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권10호
• /
• pp.5013-5034
• /
• 2019

In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.5805-5825
• /
• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.