• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.219-229
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• 2010

The PERT/CPM are considered as the base procedures for the most successful project scheduling programs. Unfortunately, it is not easy to apply these procedures to real-life projects. This is due to the fact that PERT/CPM assume an infinite number of resources for each activity in project networks. Obviously, the completion time under no constraints is less than when constraints are imposed. One way of approaching this problem is to use heuristic solution techniques. In this paper, we present three heuristics; MRU (Maximum Resource Use) rule, STU (Shortest Time Use) rule, MRUP (Max Resource Use and Period) rule for allocating resources to activities of projects under multiple resource constraints. Comparisons of the project durations show that these heuristic rules are superior to AG3 rule that has been widely used in practice (Elsayed and Boucher, 1994).

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.216-217
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• 2006

This paper presents development of program for generator maintenance scheduling. The maintenance scheduling of generating units is a dynamic discrete combinatorial optimization problem with constraints to determine the optimal maintenance periods of each generating units for a given planning periods. The developed program is designed so as to provide the maintenance schedule satisfying the operating reserve margin levelization and the procurement of proper reliability. In order to verify the effectiveness of the developed program, the numerical study has been performed with the practical data in 2005.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.798-800
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules whenever the collective maintenance schedule reported to SO by Gencos & Transco in the pool does not satisfy the specified operating criteria, such as system reliability or supply adequacy. We propose a two-layer mathematical algorithm amenable to maintenance scheduling problem into master problem and sub-problem. The master problem coordinates the scheduling, and sub-problem, DC optimal power flew, checks the adequacy. The proposed algorithm was demonstrated with a case study.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.222-224
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• 2006

This paper addresses a particle swarm optimization-based approach for solving a generating unit maintenance scheduling problem(GMS) with some constraints. We focus on the power system reliability such as reserve ratio better than cost function as the objective function of GMS problem. It is shown that particle swarm optimization-based method is effective in obtaining feasible schedules such as GMS problem related to power system planning and operation. In this paper, we find the optimal solution of the GMS problem within a specific time horizon using particle swarm optimization algorithm. Simple case study with 16-generators system is applicable to the GMS problem. From the result, we can conclude that PSO is enough to look for the optimal solution properly in the generating unit maintenance scheduling problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.9
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• pp.392-398
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• 2006

Maintenance scheduling of generating units (MSU) has strategic dimension in an oligopolistic market. Strategic MSU of gencos can affect a market power through capacity withdrawal which is related to bidding strategy in an generation wholesale market. This paper presents a combined framework that models the interrelation between competitive bidding and strategic MSU. The combined game model is represented as some sub-optimization problems of a market operator (MO) and gencos, that should be solved through bi-level optimization scheme. The gradient method with dual variables is also adopted to calculate a Nash Equilibrium (NE) by an iterative update technique in this paper. Illustrative numerical example shows that NE of a supply function equilibrium is obtained properly by using proposed solution technique. The MSU made by MO is compared with that by each genco and that under perfect competition market.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.199-208
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• 2002

The downlink rate scheduling problem is considered for CDMA networks with multiple users carrying packets of heterogeneous traffic (voice/audio only, bursty data only or mixed traffic), with each type having its own distinct quality of service requirements. Several rate scheduling algorithms are developed, the common factor of which is that part of the decision on which users to serve is based on a function of the deadline of their head-ofline packets. An approach of Andrews et al., in which the basic Earliest-Deadline-First algorithm is studied for similar systems, is extended to result in better performance by considering a more efficient power usage and by allowing service of more than one user per timeslot if the power resources permit it. Finally, the performance of the proposed schemes is compared through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1820-1831
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• 2011

When both types of periodic and aperiodic tasks are required to run on a sensor node platform with limited energy resources, we propose an energy-efficient hybrid task scheduling technique that guarantees the deadlines of real-time tasks and provides non-real-time tasks with good average response time. The proposed hybrid task scheduling technique achieved better performance than existing EDF-based DVS scheduling techniques available in the literature, the FIFO-based TinyOS scheduling technique, and the task-clustering based non-preemptive real-time scheduling technique.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1382-1389
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• 2007

This paper presents a new approach for solving the problem of maintenance scheduling of generating units using a binary particle swarm optimization (BPSO). In this paper, we find the optimal solution of the maintenance scheduling of generating units within a specific time horizon using a binary particle swarm optimization algorithm, which is the discrete version of a conventional particle swarm optimization. It is shown that the BPSO method proposed in this paper is effective in obtaining feasible solutions in the maintenance scheduling of generating unit. IEEE reliability test systems(1996) including 32-generators are selected as a sample system for the application of the proposed algorithm. From the result, we can conclude that the BPSO can find the optimal solution of the maintenance scheduling of the generating unit with the desirable degree of accuracy and computation time, compared to other heuristic search algorithm such as genetic algorithms. It is also envisaged that BPSO can be easily implemented for similar optimizations and scheduling problems in power system problems to obtain better solutions and improve convergence performance.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.277-286
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• 2019

The Unmanned Aerial Vehicle (UAV) is one of the most precious inventions of Internet of things (IOT). UAV faces the necessity to charge battery or replace battery from the charging stations during or between services. We propose scheduling algorithms for drone power charging (SADPC). The basic idea of algorithm is considering both a deadline (for increasing deadline miss ratio) and a charging time (for decreasing waiting time) to decide priority on charging station among drones. Our simulation results show that our power charging algorithm for drones are efficient in terms of the deadline miss ratio as well as the waiting time in general in compare to other conventional algorithms (EDF or SJF). Also, we can choose proper algorithms for battery charge scheduling and charge ready battery allocation according to system parameters and user requirements based on our simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.289-294
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• 2014

In this paper, we investigate the user scheduling, transmit beamforming, and receive beamforming of uplink space division multiple access (SDMA) systems where multiple users are allowed to transmit their signal to a base station (BS) using the same frequency band simultaneously. The BS performs a receive beamforming using the predetermined pseudo-random pattern and select users with a specific criterion. Especially, in this paper, we propose the threshold-based transmit power control, in which a user decrease its transmit power according if its generating interference to other users's signal is larger than a predetermined threshold. Assuming that the TDD system is used, the channel state information (CSI) can be obtained at each user from pilot signals from the BS. Simulation results show that the proposed technique significantly outperforms the existing user scheduling algorithms.