• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1608-1618
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• 2016

In this paper we introduce a graph theory approach to solve the frequency assignment problem(FAP) for military communication network. Prior algorithms are implemented adaptively to the problem, and enhanced algorithms are proposed to show that their results approximately approached the optimum performance. We also proposed polarization assignment algorithms to enhance the FAP performances.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.61-69
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• 2022

A multi-agent system is a system that aims at achieving the best-coordinated decision based on each agent's local decision. In this paper, we consider a multi agent-multi task assignment problem. Each agent is assigned to only one task and there is a completion probability for performing. The objective is to determine an assignment that maximizes the sum of the completion probabilities for all tasks. The problem, expressed as a non-linear objective function and combinatorial optimization, is NP-hard. It is necessary to design an effective and efficient solution methodology. This paper presents an approximation algorithm using submodularity, which means a marginal gain diminishing, and demonstrates the scalability and robustness of the algorithm in theoretical and experimental ways.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.51-58
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• 2015

This paper suggests assignment-swap algorithm with time complexity O(mn) to obtain the optimal solution for large-scale of transportation problem (TP) with incomplete cost lists. Generally, the TP with complete cost lists can be solved with TSM (Transportation Simplex Method). But, we can't be solved for large-scale of TP with TSM. Especially. It is hard to solve for large-scale TP with incomplete cost lists using TSM. Therefore, experts simply using commercial linear programming package. Firstly, the proposed algorithm applies assignment strategy of transportation quantity to ascending order of transportation cost. Then, we reassign from surplus of supply to shortage of demand. Secondly, we perform the 2-opt and 1-opt swap optimization to obtain the optimal solution. Upon application to $31{\times}15$ incomplete cost matrix problem, the proposed assignment-swap algorithm more improves the solution than LINGO of commercial linear programming.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.108-116
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• 2015

A missile defense system is composed of radars detecting incoming missiles aiming at defense assets, command control units making the decisions on weapon target assignment, and artillery batteries firing of defensive weapons to the incoming missiles. Although, the technology behind the development of radars and weapons is very important, effective assignment of the weapons against missile threats is much more crucial. When incoming missile targets toward valuable assets in the defense area are detected, the asset-based weapon target assignment model addresses the issue of weapon assignment to these missiles so as to maximize the total value of surviving assets threatened by them. In this paper, we present a model for an asset-based weapon assignment problem with shoot-look-shoot engagement policy and fixed set-up time between each anti-missile launch from each defense unit. Then, we show detailed linear approximation process for nonlinear portions of the model and propose final linear approximation model. After that, the proposed model is applied to several ballistic missile defense scenarios. In each defense scenario, the number of incoming missiles, the speed and the position of each missile, the number of defense artillery battery, the number of anti-missile in each artillery battery, single shot kill probability of each weapon to each target, value of assets, the air defense coverage are given. After running lpSolveAPI package of R language with the given data in each scenario in a personal computer, we summarize its weapon target assignment results specified with launch order time for each artillery battery. We also show computer processing time to get the result for each scenario.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.43-54
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• 2003

Due to insufficient available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem has become increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model, which does not satisfy the requirements ity. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then designing a sequential branch-and-bound algorithm that is made to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching for better assignments. The proposed algorithms perform well based on experimental results and they were applied to the Taiwan Cellular Cooperation (TCC) in ChungLi city to find better assignments for its network.

• Safety and Health at Work
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• v.12 no.2
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• pp.154-166
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• 2021

Background: Occupational health and safety (OHS) is a significant interest of all governments to prevent workplace hazards. Although appropriate legislation and regulations are essentials for the protection of workers, they are solely not enough. Application of them in practice should be secured by an efficient inspection system. Fundamental components of an inspection system are inspectors and their audit tasks. Maintaining the fair balanced task assignment among inspectors strictly enhances the efficiency of the overall system. Methods: This study proposes a two-phased goal programming approach for OHS inspectors' task assignments and presents a case study. Results: The solution approach gives the balanced assignment of inspectors to the workplaces in different cities of the country in the planning period. The obtained schedule takes into account the distances covered by the work places and the number of the workplaces' employees to be audited and pays attention to the human factors by considering the preferences of the inspectors. The comparisons between the obtained optimal schedule and the implemented one that is produced manually show that the approach not only maintains the technical requirements of the problem, but also provides social and physical balance to the task assignment. Conclusion: Both the approach and the application study are expected to offer fruitful inspirations in the area of safety management and policy and they provide a good guide for social policy and organizational aspects in the field of OHS inspectors' task assignment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1658-1667
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• 1994

In a cellular mobile communication control system, assignment channel for a call in a cell so as to achieve high spectral efficience is an important problem within limited frequence bandwidth. The spectral efficiency is related to the coloring problem of graph theory in a cellular mobile communication control system. In this paper, we propose channel offset scheme using a graph theory of cellular mobile communication control system and formulate chromatic bandwidth of channel offset system which is related graph coloring problem. From formulated channel assignment problem, we investgate an optimal channel offset scheme of more efficent frequence spectrum and cell design according to channel constitution and give and upper and lower bound for overall srectral bandwidth.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.41-46
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• 2017

In this paper, we investigate the D2D Transmitter(Tx) and Receiver(Rx) pair assignment problem in the cellular system where D2D users share the uplink resource of the cellular system. Sharing the uplink resource of the cellular system may cause interference to the cellular system, though it is beneficial to improve the D2D user Capacity. Therefore, to protect the cellular users, D2D transmit power should be carefully controlled. In this work, we focus on optimal Tx-Rx assignment in such a way that the total transmit power of users is minimized. First, we consider the optimum Tx-Rx assignment in general and the corresponding complexity. Then, we propose an iterative D2D Tx-Rx assignment algorithm with low complexity that can minimize total transmit power of users. Finally, we present the numerical examples that show the complexity and the convergence to the unique transmit power level.

• Journal of Information Technology Services
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• v.9 no.2
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• pp.163-177
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• 2010

In this paper, we consider a channel ordering problem that seeks to maximize the service quality in mobile radio communication systems. If a base station receives a connection request from a mobile user, one of the empty channels belonging to the base station is assigned to the mobile user. In case multiple empty channels are available, we can choose one that incurs least interference with other channels assigned to adjacent base stations. However, note that a pair of channels that are not separated enough generates interference only if both channels are assigned to mobile users. That is, interference between channels may vary depending on the channel assignment sequence for each base station and on the distribution of mobile users. To find a channel assignment sequence that seems to generate minimum interference, we develop an optimization model considering various scenarios of mobile user distribution. Simulation results show that channel assignment sequence determined by the scenario based optimization model significantly reduces the interference provided that scenarios and interference cost are properly generated.