• Communications for Statistical Applications and Methods
• /
• v.18 no.2
• /
• pp.257-266
• /
• 2011

The rapid development of airlines, has made airports busier and more complicated. The assignment of scheduled to available gates is a major issue for daily airline operations. We consider the over-constrained airport gate assignment problem(AGAP) where the number of flights exceeds the number of available gates, and where the objectives are to minimize the number of ungated flights and the total walking distance or connection times. The procedures used in this project are to create a mathematical model formulation to identify decision variables to identify, constraints and objective functions. In addition, we will consider in the AGAP the size of each gate in the terminal and also the towing process for the aircraft. We will use a greedy algorithm to solve the problem. The greedy algorithm minimizes ungated flights while providing initial feasible solutions that allow flexibility in seeking good solutions, especially in case when flight schedules are dense in time. Experiments conducts give good results.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.721-725
• /
• 2014

In this paper, we propose a fast adaptive power allocation method for an orthogonal frequency division multiple access (OFDMA) system that employs an adaptive modulation and coding (AMC) scheme. The proposed scheme aims to reduce the calculation complexity of greedy adaptive power allocation (APA), which is known as the optimal algorithm for maximizing the utility argument of power. Unlike greedy APA, which starts power allocation from "0", the proposed algorithm initially allocates a certain level of power determined by the water-filling scheme. We theoretically demonstrate that the proposed algorithm has almost the same capability of maximizing the utility argument as the greedy APA while reducing the number of operations by 2M, where M is the number of AMC levels.

• The Korean Journal of Applied Statistics
• /
• v.19 no.1
• /
• pp.149-161
• /
• 2006

The most important component in decision tree algorithm is the rule for split variable selection. Many earlier algorithms such as CART and C4.5 use greedy search algorithm for variable selection. Recently, many methods were developed to cope with the weakness of greedy search algorithm. Most algorithms have different selection criteria depending on the type of variables: continuous or nominal. However, ordinal type variables are usually treated as continuous ones. This approach did not cause any trouble for the methods using greedy search algorithm. However, it may cause problems for the newer algorithms because they use statistical methods valid for continuous or nominal types only. In this paper, we propose a ordinal variable selection method that uses Cramer-von Mises testing procedure. We performed comparisons among CART, C4.5, QUEST, CRUISE, and the new method. It was shown that the new method has a good variable selection power for ordinal type variables.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.10
• /
• pp.29-39
• /
• 2008

Greedy routing which is easy to apply to geographic wireless sensor networks is frequently used. Greedy routing works well in dense networks whereas in sparse networks it may fail. When greedy routing fails, it needs a recovery algorithm to get out of the communication void. However, additional recovery algorithm causes problems that increase both the amount of packet transmission and energy consumption. Communication void is a condition where all neighbor nodes are further away from the destination than the node currently holding a packet and it therefore cannot forward a packet using greedy forwarding. Therefore we propose a VODUA(Virtually Ordered Distance Upgrade Algorithm) as a novel idea to improve and solve the problem of void. In VODUA, nodes exchange routing graphs that indicate information of connection among the nodes and if there exist a stuck node that cannot forward packets, it is terminated using Distance Cost(DC). In this study, we indicate that packets reach successfully their destination while avoiding void through upgrading of DC. We designed the VODUA algorithm to find valid routes through faster delivery and less energy consumption without requirement for an additional recovery algorithm. Moreover, by using VODUA, a network can be adapted rapidly to node's failure or topological change. This is because the algorithm utilizes information of single hop instead of topological information of entire network. Simulation results show that VODUA can deliver packets from source node to destination with shorter time and less hops than other pre-existing algorithms like GPSR and DUA.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.3
• /
• pp.185-191
• /
• 2019

During the modern battlefields of multi-batches flight formation attack situation, it is an essential task for a commander to make a proper fire distribution of air defense missile launch platforms for threat targets with effectively and quickly. Pan et al. try to solve this problem using genetic algorithm, but they are fails. This paper gets the initial feasible solution using high threat target first destroying strategy only use 75% available fire of each missile launch platform. Then, the assigned missile is moving to another target in the case of decreasing total threat. As a result of experiment, while the proposed algorithm is polynomial-time complexity greedy algorithm but this can be improve the solution than genetic algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.46 no.1
• /
• pp.1-9
• /
• 2009

OFDM(Orthogonal Frequency Division Multiplexing) system is robust to frequency selective fading and narrowband interference in high-speed data communications. However, an OPDM signal consists of a number of independently modulated subcarriers and the superposition of these subcarriers causes a problem that can give a large PARR(Peak-to-Average Power Ratio). PTS(Partial Transmit Sequence) scheme can reduce the PAPR by dividing OFDM signal into subblocks and then multiplying the phase weighting factors to each subblocks, but computational complexity for selecting of phase weighting factors increases exponentially with the number of subblocks. Therefore, in this paper, MG-PSO(Modified Greedy algorithm-Particle Swarm Optimization) algorithm that combines modified greedy algorithm and PSO(Particle Swarm Optimization) algorithm is proposed to use for the phase control method in PTS scheme. This method can solve the computational complexity and guarantee to reduce PAPR. We analyzed the performance of the PAPR reduction when we applied the proposed method to telecommunication systems.

• The Journal of Korea Robotics Society
• /
• v.5 no.1
• /
• pp.41-47
• /
• 2010

This paper proposes a path planning method of a mobile robot in two-dimensional work space. The path planning method is based on a cell decomposition approach. To create a path which consists of a number of line segments, the Delaunay Triangulation algorithm is used. Using the cells produced by the Delaunay Triangulation algorithm, a mesh generation algorithm connects the starting position to the goal position. Dijkstra algorithm is used to find the shortest distance path. Greedy algorithm optimizes the path by deleting the path segments which detours without collision with obstacles.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.10
• /
• pp.1244-1246
• /
• 2016

Influence maximization problem is to select seed node set, which maximizes information spread in social networks. Greedy algorithm shows an optimum solution, but has a high computational cost. A few heuristic algorithms were proposed to reduce the complexity, but their performance in influence maximization is limited. In this paper, we propose general degree discount algorithm, and show that it has better performance while keeping complexity low.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.4
• /
• pp.80-87
• /
• 2022

Lack of sufficient battery capacity is one of the most important challenges impeding the development of wireless sensor networks (WSNs). Recent innovations in the areas of wireless energy transfer and rechargeable batteries have made it possible to advance WSNs. Therefore, in this article, we propose an energy-efficient charging of sensors in a WSN scenario. First, we have formulated the problem as an integer linear programming (ILP) problem. Then a utility function-based greedy algorithm named UGreedy/UF1 is proposed for solving the problem. Finally, the performance of UGreedy/UF1 is analyzed along with other baseline algorithms: UGreedy/UF2, 2-opt TSP, and Greedy TSP. The simulation results show that UGreedy/UF1 performs better than others both in terms of the deadline missing ratio of sensors and the total energy consumption of UAVs.

• Journal of Communications and Networks
• /
• v.18 no.5
• /
• pp.699-712
• /
• 2016

Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Well-known drawback of the greedy approach is that the chosen candidate is often not the optimal solution due to the myopic decision in each iteration. In this paper, we propose a tree search based sparse signal recovery algorithm referred to as the tree search matching pursuit (TSMP). Two key ingredients of the proposed TSMP algorithm to control the computational complexity are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In numerical simulations of Internet of Things (IoT) environments, it is shown that TSMP outperforms conventional schemes by a large margin.