• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.768-772
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• 2005

TSP(Traveling Salesman Problem) has been a nagging NP-complete problem to test almost every algorithmic idea in combinatorial optimization in vain. The main bottleneck is how to get the integer results {0,1} and to avoid sub-tours. We suggest simple and practical method in two steps. Firstly for every node, an initial Hamiltonian cycle us produced on the nearest neighbour concept. The node with nearest distance is to be inserted to form a increased feasible cycle. Secondly we improve the initial solution by exchanging 2 cuts of the grand tours. We got practical results within 1 from the optimum in 30 minutes for up to 200 nodes problems. TSP of real world type might be tackled practically in our formulation.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2311-2319
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• 1999

We present two heuristic algorithms for the task allocation problem (NP-complete problem) in parallel computing. The problem is to find an optimal mapping of multiple communicating tasks of a parallel program onto the multiple processing nodes of a distributed-memory multicomputer. The purpose of mapping these tasks into the nodes of the target architecture is the minimization of parallel execution time without sacrificing solution quality. Many heuristic approaches have been employed to obtain satisfactory mapping. Our heuristics are based on genetic algorithms and simulated annealing. We formulate an objective function as a total computational cost for a mapping configuration, and evaluate the performance of our heuristic algorithms. We compare the quality of solutions and times derived by the random, greedy, genetic, and annealing algorithms. Our experimental findings from a simulation study of the allocation algorithms are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.207-215
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• 2015

This paper proposes a solution-yielding linear time algorithm to NP-complete Sudoku, to which no polynomial time algorithm has been proposed. The proposed algorithm is performed on blocks in the descending order of the number of clues they contain. It firstly determines all numbers that could possibly occur in the blank rows and columns of each block. By deriving an intersecting value of corresponding rows and columns, it assigns the final number for each blank. When tested on the traditional $9{\times}9$ Sudoku, the proposed algorithm has succeeded in obtaining the solution through performance of 9 times, the exact number of the blocks. Test results on modified Jigsaw Sudoku (9 blocks) and Hypersudoku (13 blocks) also show its success in deriving the solutions by execuring 9 and 13 times respectively. Accordingly, this paper proves that the Sudoku problem is in fact P-problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.13-20
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• 1994

We consider the satellite cluster scheduling problem which is one of the most interesting problems in satellite communication scheduling area. This problem is known to be NP-complete and a couple of heuristic algorithms had been developed. In this paper, we suggest another algorithm for this problem which has the same computational complexity as the best existing one and provides much better solution quality. Extensive computational simulation results are reported.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.204-212
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• 2008

We study the routing problem in all-wireless networks based on cooperative transmissions. We model the minimum-energy cooperative path (MECP) problem and prove that this problem is NP-complete. We hence design an approximation algorithm called cooperative shortest path (CSP) algorithm that uses Dijkstra's algorithm as the basic building block and utilizes cooperative transmissions in the relaxation procedure. Compared with traditional non-cooperative shortest path algorithms, the CSP algorithm can achieve a higher energy saving and better balanced energy consumption among network nodes, especially when the network is in large scale. The nice features lead to a unique, scalable routing scheme that changes the high network density from the curse of congestion to the blessing of cooperative transmissions.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.911-914
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• 2003

The prevention of D-Dos Attack requires to install filters at As border routers. This follows that finding minimum number of filters - VC(Vertex Cover), which is NP-complete problem. So, We propose improved 'Approximate VC' which is more efficient to real AS topology using topology property. Simulation shows that our algorithm, improved 'Approximated VC' enables us to reduce 25% VC nodes in comparison with 'Approximated VC'.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.3063-3072
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• 1993

The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12B
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• pp.1066-1080
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• 2003

In this paper a scalable QoS routing scheme for distributed multimedia applications in a hierarchical wide area network is proposed. The problem of QoS routing is formulated as a multicriteria shortest path problem, known as NP-complete. The proposed hierarchical routing scheme consists of two phases. In Phase 1, every border node periodically pre-computes the QoS distance for the paths between every pair of border nodes in any level of domain hierarchy. This phase is independet of the QoS request from an application. In Phase II, distributed graph construction algorithm is performed to model the network as a graph by retrieving pre-computed QoS distances. The graph is constructed by the on-demand algorithm and contains a part of the network topology which is completely neglected or partially considered by existing routing schemes, thus maintaining more accurate topology information. By using retrieval approach rather than advertising one, no global QoS state information exchange among nodes is needed. In this Phase, distributed partition algorithm for QoS routing problem is also performed, thus eliminating virtual links on the hierarchically complete path.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.181-188
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• 2007

Undirected Rural Postman Problem(URPP) is a problem that finds a shortest tour traversing the given arcs at least once in a given network. The URPP is one of the basic network problems used in solving the various real-world problems. And it is known as NP-Complete. URPP is an arc-oriented problem that the direction of a tour in an arc has to be considered. Hence, In URPP, it is difficult to use the algorithm for Traveling Salesman Problem (TSP), which is a node-oriented problem, directly. This paper proposes the decoding algorithm using graph transformation in the genetic algorithm for URPP. That is, you can find the entire tour traversing without considering the direction of arcs by transforming the arc-oriented graph into the node-oriented graph. This paper compares the performances of the proposed algorithm with an existing algorithm. In the simulation results, the proposed algorithm obtained better than the existing algorithm

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.9-14
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• 2022

This paper presents a subset sum problem (SSP) algorithm which takes the time complexity of O(nlogn). The SSP can be classified into either super-increasing sequence or random sequence depending on the element of Set S. Additive algorithm that runs in O(nlogn) has already been proposed to and utilized for the super-increasing sequence SSP, but exhaustive Brute-Force method with time complexity of O(n2ⁿ) remains as the only viable algorithm for the random sequence SSP, which is thus considered NP-complete. The proposed subtractive algorithm basically selects a subset S comprised of values lower than target value t, then sets the subset sum less the target value as the Residual r, only to remove from S the maximum value among those lower than t. When tested on various super-increasing and random sequence SSPs, the algorithm has obtained optimal solutions running less than the cardinality of S. It can therefore be used as a general algorithm for the SSP.