• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.150-160
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• 2020

In this paper, we introduce a pilot's scheduling model which is able to maintain and balance their capabilities for each relevant skill level in military helicopter squadron. Flight scheduler has to consider many factors related pilot's flight information and spends a lot of times and efforts for flight planning without scientific process depending on his/her own capability and experience. This model reflected overall characteristics that include pilot's progression by basis monthly and cumulative flight hours, operational recent flight data and quickly find out a pinpoint areas of concern with respect to their mission subjects etc. There also include essential several constraints, such as personnel qualifications, and Army helicopter training policy's constraints such as regulations and guidelines. We presented binary Integer Programming (IP) mathematical formulation for optimization and demonstrated its effectiveness by comparisons of real schedule versus model's solution to several cases experimental scenarios and greedy random simulation model. The model made the schedule in less than 30 minutes, including the data preprocessing process, and the results of the allocation were more equal than the actual one. This makes it possible to reduce the workload of the scheduler and effectively manages the pilot's skills. We expect to set up and improve better flight planning and combat readiness in Korea Army aviation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1849-1876
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• 2022

Wireless Sensor Network (WSN) is considered as an integral part of the Internet of Things (IoT) for collecting real-time data from the site having many applications in industry 4.0 and smart cities. The task of nodes is to sense the environment and send the relevant information over the internet. Though this task seems very straightforward but it is vulnerable to certain issues like energy consumption, delay, throughput, etc. To efficiently address these issues, this work develops a cross-layer model for the optimization between MAC and the Network layer of the OSI model for WSN. A high value of duty cycle for nodes is selected to control the delay and further enhances data transmission reliability. A node measurement prediction system based on the Kalman filter has been introduced, which uses the constraint based on covariance value to decide the scheduling scheme of the nodes. The concept of duty cycle for node scheduling is employed with a greedy data forwarding scheme. The proposed Duty Cycle-based Greedy Routing (DCGR) scheme aims to minimize the hop count, thereby mitigating the energy consumption rate. The proposed algorithm is tested using a real-world wastewater treatment dataset. The proposed method marks an 87.5% increase in the energy efficiency and reduction in the network latency by 61% when validated with other similar pre-existing schemes.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.196-203
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• 2022

The resource constrained scheduling problem (RCSP) constitutes one of the most challenging problems in Project Management, as it combines multiple parameters, contradicting objectives (project completion within certain deadlines, resource allocation within resource availability margins and with reduced fluctuations), strict constraints (precedence constraints between activities), while its complexity grows with the increase in the number of activities being executed. Due to the large solution space size, this work investigates the application of Genetic Algorithms to approximate the optimal resource alolocation and obtain optimal trade-offs between different project goals. This analysis uses the cost of exceeding the daily resource availability, the cost from the day-by-day resource movement in and out of the site and the cost for using resources day-by-day, to form the objective cost function. The model is applied in different case studies: 1 project consisting of 10 activities, 4 repetitive projects consisting of 40 activities in total and 16 repetitive projects consisting of 160 activities in total, in order to evaluate the effectiveness of the algorithm in different-size solution spaces and under alternative optimization criteria by examining the quality of the solution and the required computational time. The case studies 2 & 3 have been developed by building upon the recurrence of the unit/sub-project (10 activities), meaning that the initial problem is multiplied four and sixteen times respectively. The evaluation results indicate that the proposed model can efficiently provide reliable solutions with respect to the individual goals assigned in every case study regardless of the project scale.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.856-867
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• 2006

This paper proposes a new algorithm for opportunistic scheduling that take advantage of both multiuser diversity and power control. Motivated by the multicast RTS and priority-based CTS mechanism of OSMA protocol, we propose an opportunistic packet scheduling with power control scheme based on IEEE 802.11 MAC protocol. The scheduling scheme chooses the best candidate receiver for transmission by considering the SINR at the nodes. This mechanism ensures that the transmission would be successful. The power control algorithm on the other hand, helps reduce interference between links and could maximize spatial reuse of the bandwidth. We then formulate a convex optimization problem for minimizing power consumption and maximizing net utility of the system. We showed that if a transmission power vector satisfying the maximum transmission power and SINR constraints of all nodes exist, then there exists an optimal solution that minimizes overall transmission power and maximizes utility of the system.

• Journal of the Korean Institute of Navigation
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• v.20 no.1
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• pp.27-46
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• 1996

Vessles 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 in slight ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a textbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charterer's market. This implys 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. The TS-DSS is defined as the 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 scenarios and thereby the effectiveness of TS-DSS is validated satifactorily. The authors conclude the paper with the comments on the need of appropriate support environment such as data-based DSS and network system for succesful implementation of the TS-DSS.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.646-655
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• 2008

A main issue about production management of shipyards is to efficiently manage the work in process and logistics. However, so far the management of a transporter for moving building blocks has not been efficiently performed. To solve the issues, optimal block transporting scheduling system is developed for minimizing of the travel distance without overload of a transporter. To implement the developed system, a hybrid optimization algorithm for an optimal block transportation scheduling is proposed by combining the genetic algorithm and the ant algorithm. Finally, to evaluate the applicability of the developed system, it is applied to a block transportation scheduling problem of shipyards. The result shows that the developed system can generate the optimal block transportation scheduling of a transporter which minimizes the travel distance without overload of the transporter.

• ETRI Journal
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• v.33 no.6
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• pp.857-863
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• 2011

Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy-efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3A
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• pp.248-255
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• 2008

In an OFDMA system the performance of multi-user scheduling in the frequency domain is affected by the frequency selectivity of the channel. If the channel is too flat in the frequency domain, the multi-user scheduling gain might be degraded. On the contrary, if the frequency selectivity is too high and the magnitude of the frequency response severely fluctuates on the allocation bandwidth, it is also hard to get sufficient scheduling gain. For maximizing the multi-user scheduling gain, a cyclic delay diversity technique can be used to adjust the frequency selectivity of the channel. This paper proposes a method to determine the optimal delay value of cyclic delay diversity according to the allocation bandwidth and the channel characteristics.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.220-223
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• 2011

For successfully commercialized grid systems, it is required to provide an efficient scheduling scheme which is able to optimize benefits for three participants such as consumers, brokers, and providers so that every participant has sufficient benefit to maintain a sustainable market. In this paper, we define this job scheduling problem as an objective optimization problem for three participants. The three objectives are to maximize the success rate of job execution, total achieved profit, and the system utilization. To address the scheduling problem, we propose heuristics referred to as SLA-aware scheduling scheme (SA) for optimal resource allocation. The simulation results show that the improvement and the effectiveness of the proposed scheme and the proposed scheme can outperform well-known scheduling schemes such as first come first serve (FCFS), shortest job first (SJF), and earliest deadline first (EDF).