• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.517-519
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• 2003

하드웨어 검증과 모델 체킹 등의 분야에서, SAT(satisfiability problem)나 항진 명제 검사(tautology checking)는 매우 중요한 문제이다. 그러나 이들은 모두 NP-complete 문제이므로 그 복잡도가 매우 크다. 이를 해결하기 위한 여러 연구가 진행되고 있고, 그 결과 성능이 좋은 solver들이 개발되었다. 하지만 문제가 커질수록 solver의 처리 시간이 급격하게 증가한다. 이 논문에서는 solver가 복잡한 문제를 더 효율적으로 풀기 위해 논문“Local search for Boolean relations on the basis of unit propagation”［5］에서 제안된 preprocessor(전처리기), P_EQ의 개념을 설명하고, 실험을 통한 결과를 제시한다.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.146-158
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• 1991

In this paper, we deal with the TSP (Traveling Salesperson Problem) which is well-known as NP-complete optimization problem. the TSP is applicable to network routing. task allocation or scheduling. and VLSI wiring. Well known numerical methods such as Newton's Metheod. Gradient Method, Simplex Method can not be applicable to find Global Solution but the just give Local Minimum. Exhaustive search over all cyclic paths requires 1/2 (n-1) ! paths, so there is no computer to solve more than 15-cities. Heuristic algorithm. Simulated Annealing, Artificial Neural Net method can be used to get reasonable near-optimum with polynomial execution time on problem size. Therefore, we are able to select the fittest one according to the environment of problem domain. Three methods are simulated about symmetric TSP with 30 and 50-city samples and are compared by means of the quality of solution and the running time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.409-416
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• 2003

We consider the problem of grouping orders into lots. The problem is modelled by a graph G = (V, E). where each node $\nu\;\in\;V$ denotes order specification and its weight $\omega(\nu)$ the orders on hand for the specification. We ran construct a lot simply from orders or single specification For a set of nodes (specifications) $\theta\;\subseteq\;V$, if the distance or any two nodes in $\theta$ is at most d, it is also possible to make a lot using orders on the nodes. The objective is to maximize the number of lots with size exactly $\lambda$. In this paper, we prove that our problem is NP-Complete when d = 2, $\lambda\;=\;3$ and each weight is 0 or 1. Moreover, it is also shown to be NP-Complete when d = 1, $\lambda\;=\;3$ and each weight is 1, 2 or 3

• 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'.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.505-507
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• 2003

SAT 문제는 하드웨어/소프트웨어 검증과 모델 체킹 등 다양한 분야에서 유용하게 사용되고 있으나 복잡도가 NP-complete 라는 어려움을 가지고 있다. 다양한 알고리즘과 휴리스틱, 도구들이 개발되었지만 그럼에도 불구하고 해결할 수 없는 hard instance 들이 존재한다. 이 논문에서는 그러한 hard instance를 해결하기 위한 방법의 하나로 model accumulation을 제안한다.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.165-170
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• 2023

This paper proposes an algorithm that can obtain a solution with linear time for a set cover problem(SCP) in which there is no polynomial time algorithm as an NP-complete problem so far. Until now, only heuristic greed algorithms are known to select sets that can be covered to the maximum. On the other hand, the proposed algorithm is a competitive algorithm that applies an inclusion-exclusion principle rule to N nodes up to 2nd or 3rd in the maximum number of elements to obtain a set covering all k nodes, and selects the minimum cover set among them. The proposed algorithm compensated for the disadvantage that the greedy algorithm does not obtain the optimal solution. As a result of applying the proposed algorithm to various application cases, an optimal solution was obtained with a polynomial time of O(kn²).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.157-162
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• 2023

To NP-complete 3-SAT problem, this paper proposes a O(nm) polynomial time algorithm, where n is the number of literals and m is the total frequency of all literals in equation f. The algorithm firstly decides a truth value of a literal in sequence of previously-set priority. The priority order is as follows: a literal whose occurrence in a clause is 1(k=1), a literal which is k≥2 and whose truth value is either 0 or 1, and a literal with the minimum frequency. Then, literals whose truth value is determined are then deleted from clause T and the remaining clauses. This process is repeated l times, the number of literals. As a result, the proposed algorithm has been successful in accurately determining the satisfiability of a given equation f and in deciding the truth value of all the literals. This paper, therefore, provides not only a linear-time algorithm as a viable solution to the SAT problem, but also a basis for solving the P versus NP problem.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.135-139
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• 2009

The problems to compute the distances or similarities of multiple strings have been vigorously studied in such diverse fields as pattern matching, web searching, bioinformatics, computer security, etc. One well-known method to compare multiple strings in the given set is finding a consensus string which is a representative of the given set. There are two objective functions that are frequently used to find a consensus string, one is the radius and the other is the consensus error. The radius of a string x with respect to a set S of strings is the smallest number r such that the distance between the string x and each string in S is at most r. A consensus string based on radius is a string that minimizes the radius with respect to a given set. The consensus error of a string with respect to a given set S is the sum of the distances between x and all the strings in S. A consensus string of S based on consensus error is a string that minimizes the consensus error with respect to S. In this paper, we show that the problem of finding a consensus string based on radius is NP-complete when the distance function is a metric.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.11
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• pp.830-835
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• 2006

Because of its exponential growth of data and voice transmissions through wireless communications, efficient resource management became more important factor when we design wireless networks. One of those limited resources in the wireless communications is frequency bandwidth. As a solution of increasing reusability of resources, the efficient frequency assignment problems on wireless networks have been widely studied. One suitable approach to solve these frequency assignment problems is transforming the problem into traditional graph coloring problems in graph theory. However, most of frequency assignments on arbitrary network topology are NP-Complete problems. In this paper, we consider the Chromatic Bandwidth Problem on the cellular topology wireless networks. It is known that the lower bound of the necessary number of frequencies for this problem is $O(k^2)$. We prove that the lower bound of the necessary number of frequencies for the Chromatic Bandwidth Problem is $O(k^3)$ which is tighter lower bound than the previous known result.