• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.1-8
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• 2010

This paper presents global and optimal solution for weapon assignment problems using the Munkres assignment algorithm. We propose a new modeling method of weapon assignment problems concerning some constraints of weapon systems. In this paper, we compares the Munkres weapon assignment algorithm with two other algorithms employing a search tree model in terms of computational complexity and performance. One is an optimal algorithm using exhausted search and the other is a greedy algorithm which selects the first search result as a solution. The experiment results show that the Munkres weapon assignment algorithm has better performance and less computational complexity in comparison with the two other algorithms.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.139-147
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• 2012

This paper suggests simple search algorithm for optimal solution in assignment problem. Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm. The proposed algorithm reduces the 4 steps of Hungarian algorithm to 1 step, and only selects the minimum cost of row and column then gets the optimal solution simply. For the 27 balanced and 7 unbalanced assignment problems, this algorithm finds the optimal solution but the genetic algorithm fails to find this values. This algorithm improves the time complexity O($n^3$) of Hungarian algorithm to O(n). Therefore, the proposed algorithm can be general algorithm for assignment problem replace Hungarian algorithm.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.81-82
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• 2006

Most work on cooperative diversity has assumed that the cooperating group (source and partners) and the associated average channel conditions between terminals (source, partners, and destination) are predetermined. In practical situations, however, it is important to develop the efficient algorithms for assigning the terminals with good inter-user channels for cooperating groups. In this paper, we propose the partner assignment algorithm for cooperative diversity in mobile communication systems. The proposed partner assignment algorithm is investigated by using the path loss model for mobile communication systems. Numerical results show that the proposed partner assignment algorithm provides the comparable probability of cooperative transmission to the partner assignment algorithm using exhaustive search. The probability of cooperative transmission increases with the number of users, which gives potential benefits of practical implementation to user cooperation in mobile communication systems.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.99-113
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• 2002

The multi-class traffic assignment problem is the most typical one of the multi-solution traffic assignment problems and, recently formulation of the models and the solution algorithm have been received a great deal of attention. The useful solution algorithm, however, has not been proposed while formulation of the multi-class traffic assignment could be performed by adopting the variational inequality problem or the fixed point problem. In this research, we developed a hybrid solution algorithm which combines GA algorithm, diagonal algorithm and clustering algorithm for the multi-class traffic assignment formulated as a variational inequality Problem. GA algorithm and clustering algorithm are introduced for the wide area and small cost. We also performed an experiment with toy network(2 link) and tested the characteristics of the suggested algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.53-63
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• 2022

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme "dual-stage Hungarian-based assignment algorithm". Furthermore, we also propose deep learning (DL) based deep neural network (DNN)scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme providessimilar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.163-171
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• 2013

This paper proposes an algorithm that seeks the optimal solution for an assignment problem through a simplified process. Generally it is Hungarian algorithm that is prevalently used to solve a given assignment problem. The proposed algorithm reduces 4 steps Hungarian algorithm into 2 steps. Firstly, the algorithm selects the minimum cost from a matrix and deletes the rest of the rows and columns. Secondly, it improves on the solution through reassignment process. For 27 balanced assignment problems and 7 unbalanced problems, the proposed algorithm has successfully yielded the optimal solution, which Genetic algorithm has failed. This algorithm is thus found to be an appropriate replacement of Hungarian algorithm.

• ETRI Journal
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• v.25 no.4
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• pp.211-218
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• 2003

This paper presents a dynamic resource allocation algorithm with multi-frequency time-division multiple access for the return link of interactive satellite multimedia networks such as digital video broadcasting return channel via satellite systems. The proposed timeslot assignment algorithm, called the very efficient dynamic timeslot assignment (VEDTA) algorithm, gives an optimal assignment plan within a very short period. The optimality and computational efficiency of this algorithm demonstrate that it will be useful in field applications.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.105-112
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• 2015

Generally, the optimal solution of assignment problem has been obtained by Hungarian algorithm with O($n^3$) time complexity. This paper proposes more simple algorithm with O($n^2$) time complexity than Hungarian algorithm. The proposed algorithm simply selects minimum cost in each row, and classified into set S, H, and T. Then, the minimum cost is moved from S to T and $S{\rightarrow}H$, $H{\rightarrow}T$. The proposed algorithm can be obtain the same optimal solution as well-known algorithms and improve the optimal solution of partial unbalanced assignment problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.68-82
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• 2011

Wireless mesh networks (WMNs) provide high-speed backbone networks without any wired cable. Many researchers have tried to increase network throughput by using multi-channel and multi-radio interfaces. A multi-radio multi-channel WMN requires channel assignment algorithm to decide the number of channels needed for each link. Since the channel assignment affects routing and interference directly, it is a critical component for enhancing network performance. However, the optimal channel assignment is known as a NP complete problem. For high performance, most of previous works assign channels in a centralized manner but they are limited in being applied for dynamic network environments. In this paper, we propose a simple flow estimation algorithm and a hybrid channel assignment algorithm. Our flow estimation algorithm obtains aggregated flow rate information between routers by packet sampling, thereby achieving high scalability. Our hybrid channel assignment algorithm initially assigns channels in a centralized manner first, and runs in a distributed manner to adjust channel assignment when notable traffic changes are detected. This approach provides high scalability and high performance compared with existing algorithms, and they are confirmed through extensive performance evaluations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.141-151
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• 2012

This paper suggests more simple algorithm than Hungarian algorithm for assignment problem. Hungarian algorithm selects minimum cost of row and column, and subtracts minimum cost from each cost. Then, performs until the number of minimum lines with 0 equals the number of rows. But, the proposed algorithm selects the minimum cost for each rows only. From the start point with over 2 to the target point with null selects in column, fixes the maximum opportunity cost that the difference of the cost of starting point and target point, and moves the cost less than opportunity cost th more than previous cost. For the 25 balance and 7 unbalance assignment problems, This algorithm gets the optimal solution same as Hungarian algorithm. This algorithm improves the time complexity $O(n^3)$ of Hungarian algorithm to $O(n^2)$, and do not performs the transformation process from unbalance to balance assignment in Hungarian algorithm. Therefore, this algorithm can be alter Hungarian algorithm in assignment problem.