• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.209-214
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• 2020

The equitable partitioning problem(EPP) is classified as [0/1] binary skill existence or nonexistence and integer skill levels such as [1,2,3,4,5]. There is well-known a polynomial-time optimal solution finding algorithm for binary skill EPP. On the other hand, tabu search a kind of metaheuristic has apply to integer skill level EPP is due to unknown polynomial-time algorithm for it and this problem is NP-hard. This paper suggests heuristic greedy algorithm with polynomial-time to find the optimal solution for integer skill level EPP. This algorithm descending sorts of skill level frequency for each field and decides the lower bound(LB) that more than the number of group, packing for each group bins first, than the students with less than LB allocates to each bin additionally. As a result of experimental data, this algorithm shows performance improvement than the result of tabu search.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.381-388
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• 1997

This paper proposes a heuristic algorithm to efficiently perform line balancing in the PCB assembly line including multiple surface mounters efficiently. Generally, the problems in line balancing are classified into two kinds. Firstly, is the determining of the minimum number of machines required for achieving the desired production rate. Secondly, is the assign of jobs to multiple machines in order to minimize the cycle time which is defined as a maximum among the working times of machines when the number of machines is fixed. In this paper, we deal with the latter. We consider a PCB assembly line, including the multiple surface mounters arranged serially as a target system. Also, the conveyor is assumed to move at a constant speed and have no buffer. Considering that the minimum number of machines required for the desired production rate is a discrete nonincreasing function which is inversely proportional to the cycle time, we propose an optimization algorithm for line balancing by using the binary search method. The algorithm is validated through computer simulation, the results of which show that their shapes coincide nearly with those of optimal line balancing efficiency graphs regardless of the number of components, the performance of surface mounters, and the structure of assembly line.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.1-9
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• 2005

In this paper, we suggest multi colony interaction ant reinforcement learning model. This method is a hybrid of multi colony interaction by elite strategy and reinforcement teaming applying Temporal Difference(TD) learning to Ant-Q loaming. Proposed model is consisted of some independent AS colonies, and interaction achieves search according to elite strategy(Intensification, Diversification strategy) between the colonies. Intensification strategy enables to select of good path to use heuristic information of other agent colony. This makes to select the high frequency of the visit of a edge by agents through positive interaction of between the colonies. Diversification strategy makes to escape selection of the high frequency of the visit of a edge by agents achieve negative interaction by search information of other agent colony. Through this strategies, we could know that proposed reinforcement loaming method converges faster to optimal solution than original ACS and Ant-Q.

• Journal of Navigation and Port Research
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• v.38 no.3
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• pp.299-305
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• 2014

In a ship-building, a transporter is the moving equipment to transport ship blocks from a workshop to another in a shipyard. The efficient scheduling of transporters has an important role for the operation of a building ship to be completed on schedule. There are the previous studies on the transporter scheduling for moving blocks in a shipyard. These studies have no consideration for the transporter combination to increase the productivity of moving blocks. This paper presents an efficient transporter scheduling model considering transporter combination explicitly. The objective of this model is to minimize the operational cost and maintain the workload balance among transporters. we also present three heuristics algorithms based on tabu search for finding the solution of the model. The efficiency of the proposed heuristics are verified with several computational tests.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12C
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• pp.1164-1174
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• 2007

Antenna selection based MIMO schedulers are proposed to achieve the optimal performance with low complexity in uplink multiuser MIMO/FDD system. In this paper, three heuristic schedulers are proposed to approach the optimal performance which is achieved by the optimal Brute-Force Scheduler. Two search methods called sub-set and full-set way are also discussed to set up the antenna channels to be the candidates of the scheduler. Simulation results show that the sum rate and BER performance of the proposed CSS and SOAS schemes are about the same to that of the brute-force scheduler with affordable complexity, while RC-SOAS with further reduced complexity achieves almost the optimal performance in the case of small number of antennas. Moreover, the complexity can be additionally reduced by the sub-set search method when the number of transmit and receive antennas are 2 respectively, which is applicable in the realistic systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.425-433
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• 2012

Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.856-864
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• 2019

The weapon-target assignment (WTA) problem is a matter of effectively allocating weapons to a number of threats. The WTA in a rapidly changing dynamic environment of engagement must take into account both of properties of the threat and the weapon and the effect of the previous decision. We propose a method of applying the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, a kind of meta-heuristic method, to derive optimal solution for a dynamic WTA problem. Firstly, we define a dynamic WTA problem and formulate a mathematical model for applying the algorithm. For the purpose of the assignment strategy, the objective function is defined and time-varying constraints are considered. The dynamic WTA problem is then solved by applying the GRASP algorithm. The optimal solution characteristics of the formalized dynamic WTA problem are analyzed through the simulation, and the algorithm performance is verified via the Monte-Carlo simulation.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.869-877
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• 2007

This paper proposes a realtime scheduling method using local search algorithm for non-crossable yard cranes in automated container terminal. To take into consideration the dynamic property of yard crane operation and satisfy the real time constraint, the proposed method repeatedly builds crane schedule for the jobs in a fixed length look-ahead horizon whenever a new job is requested In addition, the proposed method enables the co-operation between yard cranes through prior re-handling and re-positioning in order to resolve the workload imbalance problem between the two cranes, which is one of the primary causes that lower the performance of yard cranes. Simulation-based experiments have shown that the proposed method outperforms the heuristic based methods, and the cooperation scheme contributes a lot to the performance improvement.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.406-417
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• 2001

With the advances in multimedia databases on the World Wide Web, it becomes more important to provide users with the search capability of distributed multimedia data. While there have been many studies about the database selection and the collection fusion for text databases. The multimedia databases on the Web have autonomous and heterogeneous properties and they use mainly the content based retrieval. The collection fusion problem of multimedia databases is concerned with the merging of results retrieved by content based retrieval from heterogeneous multimedia databases on the Web. This problem is crucial for the search in distributed multimedia databases, however, it has not been studied yet. This paper provides novel algorithms for processing the collection fusion of heterogeneous multimedia databases on the Web. We propose two heuristic algorithms for estimating the number of objects to be retrieved from local databases and an algorithm using the linear regression. Extensive experiments show the effectiveness and efficiency of these algorithms. These algorithms can provide the basis for the distributed content based retrieval algorithms for multimedia databases on the Web.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6290-6296
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• 2015

More informative ones of heuristics can help to conduct search more efficiently to obtain solution plan. However, in general, to derive highly informative heuristics from problem specifications requires lots of computational effort. To address this problem, we propose an State-Action based Planning Graph(SAPG) and Action-based heuristics for solving planning problems more efficiently. The SAPG is an extended one to be applied to can find interactions between subgoal & goal conditions from the relaxed planning graph which is a common means to get heuristics for solving the planning problems, Action-based heuristics utilizing SAPG graphs can find interactions between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. Therefore Action-based heuristics have more information than the existing max and additive heuristics, also requires less computational effort than the existing overlap heuristics. In this pager. we present the algorithm to compute Action-based heuristics, and then explain empirical analysis to investigate the accuracy and the efficiency of the Action-based heuristics.